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PhD Opening (AI Safety and AI for Social Good)
University of South Florida
I am an Assistant Professor at the University of South Florida (USF) looking to recruit exceptional and motivated PhD and MS students to work on research relating to (1) AI/ML safety, (2) Generative AI alignment, and (3) using Generative AI for mitigating social media harms. There is funding available for these projects. Please reach out by email if interested.
Machine Learning Researcher
Shift Bioscience
Do you want to drive the discovery of rejuvenating interventions that can extend healthy lifespan and treat age-related disease?

I’m happy to announce we are currently hiring for a Machine Learning Research Scientist in our soon-to-open ML office in Toronto, Canada!

In this role, you will build and improve our cell simulation models, and work on algorithms that help us to prioritise potential rejuvenation interventions. Your contributions will unlock the previously impossible task of exploring the combinatorial space of safe rejuvenation.

If you are interested, please send a cover letter and your CV to lucas@shiftbioscience.com! If you are not already based in Canada, relocation and visa fees will be sponsored by Shift.
Link: https://www.linkedin.com/jobs/view/3915410702
Staff Machine Learning Researcher
Merantix Momentum
WHAT WE DO

Merantix Momentum is a Berlin-based AI startup focusing on accelerating AI adoption across many industries through publicly funded research projects as well as B2B solutions. We work across several domains, including manufacturing, the public sector, healthcare, and more, and transform businesses as an external machine learning department using our core expertise in state-of-the-art machine learning combined with our culture of rapid iterations to build scalable solutions.

YOUR ROLE

As a Staff Machine Learning Researcher, you will bring cutting-edge deep-learning methods from research into real-world applications, actively contributing to the latest developments in academia.

For more information visit our career page.
Link: https://merantix-momentum.jobs.personio.com/job/1537613?language=en&display=en
Future Computing Postdoctoral Fellowship at Rice University
Rice University
Recent advances in Generative AI have profoundly impacted fundamental tasks and research questions across the biological sciences. We are also all witnesses to breakneck progress and rapid advances in large language models. This is a joint hire across the Rush lab and Treangen lab where we are specifically looking for a candidate who will pioneer the development of novel computational tools that bring LLMs to  metagenomic analysis in an intuitive way to facilitate exploratory and hypothesis driven microbiome research.


The candidate will be based in the George R. Brown School of Engineering at Rice University, which is strongly committed to nurturing the aspirations of faculty, staff, and students in an inclusive environment. We offer a highly competitive salary, h1b visa sponsorship, benefits, travel funds, and the opportunity to pave the way for the future of metagenomic analysis.


The candidate will also work closely with members of both labs, as well as our collaborators within the Texas Medical Center, the largest medical complex in the world. Rice University is an equal opportunity employer and a Tier 1 Research University located in the vibrant urban setting of Houston, TX, the fourth largest city in the US. Rice is consistently ranked in the top 20 National Universities by US News, #9 Best Colleges in the US by Niche, and #1 for Quality of Life by the Princeton Review.



Minimum Education Required

Ph.D. or equivalent doctorate


Specify Major/Discipline

Computer science, ML, bioinformatics, or related field
Founding AI Scientist (Precision Systems Immunology)
Stealth Techbio
Immune-mediated diseases affect hundreds of millions of people world-wide, but less than 12% of new drugs reach approval, largely due to insufficient pre-clinical understanding of the complex underlying disease biology.

We are building a techbio therapeutics company aimed at disrupting drug discovery in the immunology space. Consider joining us if you want to co-create innovative tech that addresses a critical unsolved problem at the root of drug discovery: effectively exploring the causal mechanisms of disease through more realistic disease models prior to designing therapeutics.

Your role:
* Help us build a unique lab-in-the-loop AI discovery system for immunology from the ground up, influencing strategic and technical direction.
* Work with multi-modal biological data, including high-content microscopy and single cell sequencing perturbation data, to drive mechanistic understanding of disease and target discovery.
* Be part of a flat cross-functional team that deeply appreciates the challenges of each domain and is determined to make a dent.
Grow into a scientific leadership role as the company evolves.

Your profile:
* Experienced ML scientist/engineer, computational biologist, or similar - prior experience applying AI in the life sciences is a plus.
* Deeply familiar with causal inference methods, handling complex multimodal datasets, foundation model approaches and/or reinforcement learning, as well as best practices for deployment.
* Systems thinker with a proven track record of translating research into practice.

What we offer:
* The opportunity to be part of a pioneering, highly collaborative team with a purpose.
* Healthy participatory culture from the beginning: you will significantly shape company decisions, culture, and strategy.
* A compensation package including salary, benefits, and an early equity stake with substantial long-term upside.

This is optionally a hybrid/remote position with occasional on-sites that we decide on together.
Link: https://merantix.jobs.personio.de/job/1550072
Post Docs - Systems & AI
Microsoft
We are looking for a Post Docs to design novel solutions for our cloud workloads (both general purpose and ML) with a singular purpose of making them scalable, fast, reliable, and efficient. The ideal candidate will have a strong background in systems research or machine learning and the ambition to apply them to large scale production systems.

Recent publications from our group: https://www.microsoft.com/en-us/research/group/systems-innovation/publications/
Senior Researcher - Systems & AI
Microsoft
We are looking for Senior Researchers to design novel solutions for our cloud workloads (both general purpose and ML) with a singular purpose of making them scalable, fast, reliable, and efficient. The ideal candidate will have a strong background in systems research or machine learning and the ambition to apply them to large scale production systems

Recent publications from our group: https://www.microsoft.com/en-us/research/group/systems-innovation/publications/
Algorithm Research Intern
AntGroup
Ant Group - Ant Intelligent Engine Technology Division - Algorithm Intern
 

Team introduction:
 
Explore the big model paradigm that combines NLP, multimodal big models, and search recommendation basic algorithms. New models including smart assistant, search, and recommendation help Alipay users gain a new user experience.

Job Description:
 
1. Participate in the algorithm development and product application implementation of Ant NLP and multimodal large model related technologies (knowledge injection, graph inference, tuning, rlhf) for specific business scenarios and needs.
2. Actively explore the forefront of technology, encourage and support the sedimentation of research results into technical articles, patents, and academic papers

Job requirements:
1. Master‘s or doctoral students are currently studying, and excellent undergraduate students are also eligible (priority given to related majors such as artificial intelligence, machine learning, statistics, mathematics, etc. Plus)
 
2. Familiar with Python/SQL programming, intern at least one deep learning framework (Python, Tensorflow, or Keras), and develop data processing and machine learning processes based on it
3. Priority given to having knowledge and experience in pre training, finetune, and inference optimization for large models such as NLP and multimodality
 
4. Good learning and communication skills, sense of responsibility and self drive

Link: None
Applied Scientist Intern
Amazon Prime Video
We have openings in our team for interns at Prime Video working on many modalities like video, audio and text. Lots of exciting opportunities ideally for PhD students. Reach out for more information.
ML engineer
Wordbricks
We’re looking for a talented and passionate ML engineer who’s interested in building a platform using multimodal AI from scratch!
Link: https://getgpt.app
PhD in self-supervised learning with sensori-motor theories
Univ Lyon 1
In the context of the MeSMRise project, we are looking for excellent students willing to work on self-supervised learning for object learning and perception. The main originality of the project is to put action at the core of representation learning, related to equivariance learning in SSL and sensory-motor theories and embodiement in cognitive science.
Link: https://projet.liris.cnrs.fr/mesmrise/index.html
PhD position on Efficient Neural Representation of Datasets
Bosch Center for AI
We conduct research on state-of-the-art deep generative models that are used to enable real-world Bosch systems to be data-efficient. We are looking for a PhD student who is interested in researching creative applications of generative models (e.g. stable diffusion) as a controllable dataset representation for training and validating networks for downstream tasks.



Not all data points in a dataset are equally important for the performance of a neural network. As training progresses, loss on some data points might become uninformative since the network already learned what it can from it. As such, it can be advantageous to observe the network training to serve it the right type of data at the right time. However, simply selecting data from a fixed dataset could be problematic when no image with the precise mix of attributes exists. The goal of this PhD project is to develop new learning algorithms for generating relevent data “on demand” in response to the need of the target network. This includes improving training efficiency by synthesizing the most relevant data, enforcing desired invariance by creating example, etc.



- As part of our team, you will develop novel approaches to adapt deep generative models (e.g. diffusion models, GANs, VAEs) as data sources to better train and validate downstream models.

- Furthermore, you exploit the controllability and knowledge present in generative base models to move past seeing datasets as just a collection of images.

- You discuss and develop new ideas within the deep learning and computer vision experts at Bosch Center for AI.

- Finally, publications in top-tier journals and at conferences follow.
Link: https://smrtr.io/jXSVr
PhD position - Foundation Models for Improving and Auditing Data at Scale
Bosch Center for AI
We conduct cutting-edge deep learning research with a focus on data. We are looking for a motivated PhD student eager to delve into research on deep learning methods for improving and auditing data, as well as to explore their real-world applications for further improving the performance, reliability, and efficiency of AI models.



The goal of this position is to develop novel and automated data auditing methods, leveraging foundation models. These methods shall enable data analysis at scale, provide insights into models’ generalization capabilities and aid performance estimation in new domains. Additionally, outcomes from data auditing will be utilized to improve data quality, e.g., pruning less relevant samples, adding more valuable ones, and generating advanced annotations to expedite learning with smaller models and model evaluation.

As a PhD student in our team, you will innovate and automate data auditing methodologies for analyzing data diversity, coverage as well as biases, leveraging deep generative models and foundation models.
In addition, you will advance data filtering and annotation strategies to optimize training efficiency as well as streamline model evaluation processes.
You collaborate with Machine Learning as well as Computer Vision experts and publish in top-tier journals as well as conferences.
Furthermore, you will discuss and develop new ideas within the Deep Learning research team at Bosch Corporate Research (CR).
You will be co-advised by a senior expert at Bosch and a university professor. The final PhD topic will be aligned with both sides, aiming at awesome research that has tangible real-world applications and impacts.
Link: https://jobs.smartrecruiters.com/BoschGroup/743999983362944-phd-foundation-models-for-improving-and-auditing-data-at-scale
Machine Learning Compiler Engineer
Gensyn
Responsibilities:
👉 Lower deep learning graphs - from common frameworks (PyTorch, Tensorflow, Keras, etc) down to an IR representation for training - with particular focus on ensuring reproducibility
👉 Write novel algorithms - for transforming intermediate representations of compute graphs between different operator representations.
👉 Ownership - of two of the following compiler areas:
Front-end - deal with the handshaking of common Deep Learning Frameworks with Gensyn's IR for internal IR usage. Write Transformation passes in ONNX to alter IR for middle-end consumption
Middle-end - write compiler passes for training-based compute graphs, integrate reproducible Deep Learning kernels into the code generation stage, and debug compilation passes and transformations as you go
Back-end: lower IR from middle-end to GPU target machine code

Minimum Requirements:
✅ Compiler knowledge - base-level understanding of a traditional compiler (LLVM, GCC) and graph traversals required for writing code for such a compiler
✅ Solid software engineering skills - practicing software engineer, having significantly contributed to/shipped production code
✅ Understanding of parallel programming - specifically as it pertains to GPUs
✅ Strong willingness to learn Rust - as a Rust by default company, we require that everyone learns Rust so that they have context/can work across the entire codebase
✅ Ability to operate on:
High-Level IR/Clang/LLVM up to middle-end optimisation; and/or
Low Level IR/LLVM targets/target-specific optimisations - particularly GPU specific optimisations
✅ Highly self-motivated with excellent verbal and written communication skills
✅ Comfortable working in an applied research environment - with extremely high autonomy
Link: https://www.gensyn.ai/jobs?ashby_jid=6ee9f1c1-7fe5-4728-aa3f-9686c86cebdf
Machine Learning Researcher
Gensyn
Responsibilities
👉 Train highly distributed models - over uniquely decentralised and heterogeneous infrastructure, rather than GPU clusters
👉 Research novel model architectures - design, build, test, and iterate over completely new ways of building neural networks; with an eye towards achieving byzantine tolerance in a trustless compute setting
👉 Publish & collaborate - write research papers targeting top-tier AI conferences such as AAAI, ICML, IJCAI and NIPS, and collaborate with experts from universities and research institutes
👉 Engineering support - work with the engineering team on wider issues concerning ML (e.g. reproducible training)
👉 Follow best practices - build in the open with a keen focus on designing, testing, and documenting your code
👉 Write & engage - contribute to technical reports/papers describing the system and discuss with the community

Minimum requirements
✅ Extremely strong research background - with publications at major machine learning conferences (or commensurate industrial experience)
✅ Strong background in machine learning and distributed systems
✅ Hands-on experience with distributed model training
✅ Highly self-motivated with excellent verbal and written communication skills
✅ Comfortable working in an applied research environment - with extremely high autonomy and unpredictable timelines

Nice to haves
🔥 Communication backend experience - e.g. NCCL, GLOO and MPI
🔥 Experience training Large Language Models (LLMs)
Link: https://www.gensyn.ai/jobs?ashby_jid=019d61e6-a59d-47a3-83d4-bde2ce4b358f
LLM Research Intern, Baidu ERNIE
Baidu
【Internship Opportunity in Beijing】Baidu NLP Department | ERNIE LLM Research Intern

About us:
The Baidu ERNIE Model Team is dedicated to researching and applying pre-training techniques for large models, possessing profound technical expertise in this domain. Since its inception in 2019, the ERNIE team has achieved numerous breakthroughs in text, code, multimodal fields, including ERNIE 1.0/2.0/3.0/3.5/4.0, ERNIE-Bot, ERNIE-M, ERNIE-Code, ERNIE-Vil/ViLG, ERNIE-Music, among others. Multiple achievements have been published in academic conferences such as ACL, EMNLP, NAACL, ICLR, ICML, AAAI, IJCAI, CVPR, topping prestigious lists like GLUE and SuperGLUE, and securing over ten championships in public semantic evaluations.

Job Responsibilities

1. Engage in forward-looking algorithm research for generative large models, including but not limited to multimodal, RLHF alignment, multilingual, etc.
2. Author/publish high-level academic papers.

Job Requirements:

1. Currently pursuing a Ph.D. or Master’s degree with research focus on large models, NLP, with consent from academic advisor for internship participation. Applicants must have completed comprehensive research training.
2. Proficient in algorithm implementation, adept in at least one deep learning framework; experience with distributed frameworks is preferred.
3. Strong engineering skills, with relevant experience in generative language models.
Full-time internship, duration of at least 6 months (critical).
4. At least one of the following must be met:
1. Published first-author papers at academic conferences in NLP/ML domains (including but not limited to ACL/EMNLP, ICML/ICLR/NeurIPS, ICCV/ECCV/TPAMI), or have influential open-source projects.
2. Experience or internship in large model training, familiarity with distributed frameworks like deepseed, capable of rapidly reproducing existing methods.

Location: Beijing (onsite)
contact: [chaiyekun@baidu.com](mailto:chaiyekun@baidu.com)
Link: None
PhD Position (Collaborative Learning, Optimization at Scale)
CISPA Helmholtz Center
The research group led by Sebastian Stich at the Helmholtz Center CISPA in Saarbrücken (Germany) has an open PhD position for a 4-year PhD program.

Possible research topics during your PhD include theory and algorithms for
- federated and collaborative learning
- privacy preserving machine learning
- fairness, robustness, personalization
- efficient training methods for transformer models
- learning from medical data (the position can be associated with a Helmholz AI research project)

The position is fully funded and comes with excellent working conditions, such as a competitive salary, social security, 30 days of vacation, spacious offices, and generous travel support. Participation in teaching is encouraged, but not required.

**Contact**
In case you attend ICLR 2024 in Vienna, please contact Sebastian Stich to chat in person.

**About CISPA**
The CISPA Helmholtz Center for Information Security provides a unique work environment that offers the advantages of a university department and a research laboratory alike. As the latest member of the Helmholtz Association, the largest research organization in Germany, CISPA has embarked on a mission: to rethink the digitalized world of the future from the ground up and make it safer through innovative cutting-edge research. CISPA is located in Saarbrücken, in the tri-border area of Germany, France, and Luxembourg. We maintain an international and diverse work environment and seek applications from outstanding researchers worldwide. The working language is English. A command of German is not required for a successful career at CISPA. CISPA is an equal opportunity employer.

Link: https://sstich.ch/
Postdoc Position
CISPA Helmholtz Center
The research group led by Sebastian Stich at the Helmholtz Center CISPA in Saarbrücken (Germany) welcomes applications for a postdoctoral position.

**Description**

Candidates should have completed, or be near completion of, a PhD with a strong international publication record in areas such as (but not limited to) applied or theoretical machine learning, optimization, natural language processing, etc. They will lead innovative research projects in a stimulating, open, and international research environment with a highly talented and motivated team, embedded in a strong network of academic and industrial collaborators.

Ability and motivation to co-lead applied (interdisciplinary) projects e.g. in collaboration with medicine, industry or other sciences is a plus, but not a requirement.

In case you will attend ICLR 2024 in Vienna, please reach out to Sebastian Stich to chat in person.

**About CISPA**
The CISPA Helmholtz Center for Information Security provides a unique work environment that offers the advantages of a university department and a research laboratory alike. As the latest member of the Helmholtz Association, the largest research organization in Germany, CISPA has embarked on a mission: to rethink the digitalized world of the future from the ground up and make it safer through innovative cutting-edge research. CISPA is located in Saarbrücken, in the tri-border area of Germany, France, and Luxembourg. We maintain an international and diverse work environment and seek applications from outstanding researchers worldwide. The working language is English. A command of German is not required for a successful career at CISPA. CISPA is an equal opportunity employer.

Link: https://sstich.ch/
PhD and PostDoc Positions (Trustworthy AI & AI Security)
CISPA Helmholtz Center for Information Security
We are hiring! Multiple openings for PhD and PostDoc positions on Trustworthy AI, AI Security, LLM, Safety, Robustness, and Privacy. Please reach out: cispa.saarland/group/fritz/
Link: cispa.saarland/group/fritz/
Applied Researcher II
Capital One
At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
Link: https://capitalone.wd1.myworkdayjobs.com/Capital_One/job/McLean-VA/Applied-Researcher-II_R178113-1
Applied Researcher I
Capital One
At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
Link: https://capitalone.wd1.myworkdayjobs.com/Capital_One/job/McLean-VA/Applied-Researcher-I_R179400-1
Looking for motivated students that want to do PhD.
Australian National University
We are looking for new PhD students for the upcoming scholarship round (application due on 31st August 2024) at the
Australian National University (ANU is ranked #34 in the QS Ranking).
To succeed, you need an outstanding publication record, e.g., one or more first-author papers in venues such CVPR, ICCV,
ECCV, AAAI, ICLR, NeurIPS, ICML, IJCAI, ACM KDD, ACCV, BMVC, ACM MM, IEEE. Trans. On Image Processing, CVIU, IEEE
TPAMI, or similar (the list is non-exhaustive). Non-first author papers will also help if they are in the mix. Some patents
and/or professional experience in Computer Vision, Machine Learning or AI are a bonus. You also need a good GPA to
succeed.
We are looking for new PhD students to work on new problems that may span over fine-tuning and adapting Foundation
Models, LLMs, diffusion models or design of Graph Neural Networks, design of new (multimodal) Self-supervised Learning
and Contrastive Learning Models (images, text, videos, graphs, time series, etc. ) or Adversarial and/or Federated learning
or other contemporary fundametnal/applied problems (e.g., learning without backprop, adapting FMs to be less resource
hungry, proteine property prediction, structured output generative models, visual relation inference etc.)
In general, we are open to discussing your interests and topics (be it open category detection or segmentation, action
recognition, anomaly detection, node classification, collaborative filtering, incremental learning, hyperbolic geometry,
adversarial learning or federated learning, or generative models such as adapting stable diffusion or scoring function
models, or other related topics), if you reach out, we can discuss what is possible.

If you are interested, reach out for an informal chat with Assoc. Prof. Dr. Koniusz. I am at ICLR if you want to
chat?): piotr.koniusz@data61.csiro.au (or piotr.koniusz@anu.edu.au, www.koniusz.com)
Link: www.koniusz.com
(Research) Engineer at Stealth Startup
Stealth Startup
We are a team working on security for autonomous AI systems. We are looking for a motivated team member to join us in Zurich Switzerland. Ideally an applicant brings experience and interest with LLMs, LLM-Based Agents or Secure/Trustworthy ML. If you are interested we are happy to meet up and share more!
Link: None
Applied Scientist 2
Qualtrics
The Data Intelligence Center of Excellence (DICE) organization provides AI/ML research and development services for all product lines. This team builds core machine learning infrastructure and services.

DICE team is looking for talented and innovative Applied Scientist to bring our Machine Learning and Artificial Intelligence R&D and strategy to the next level. Our goal is to personalize the Qualtrics experience using ML and AI features showcasing Qualtrics data as a core value proposition and competitive advantage.

As a Machine Learning Applied Scientist at Qualtrics, you should love building cutting-edge predictive models to solve hard customer problems. Crafting models in an agile environment to withstand hyper growth and owning quality from end-to-end is a rewarding challenge and one of the reasons Qualtrics is such an exciting place to work!
Link: https://www.qualtrics.com/careers/us/en/job/QUALUS5922451EXTERNALENUS/Applied-Scientist-II?
AI Applied Research Intern
Translated

The "AI Applied Research Intern" position at Translated offers a unique opportunity to contribute to cutting-edge advancements in Text-to-Speech (TTS) technology. Translated is a professional translation provider aiming to enable universal understanding across languages. The role involves working closely with the AI Research team to develop TTS technology for Translated's innovative products, including video dubbing and expressive speech synthesis.

Responsibilities include implementing state-of-the-art Deep Learning algorithms, building robust training pipelines, designing and conducting experiments, evaluating results, and staying updated with the latest advancements in Deep Learning. Candidates should be enrolled in or recent graduates of master's or PhD programs in relevant STEM disciplines, with hands-on experience in Deep Learning projects and proficiency in Python and Deep Learning libraries like PyTorch. Experience in speech and language technology, multi-GPU training, and open-source contributions are advantageous.

The internship takes place at Translated's headquarters in Pi Campus, Rome, offering a dynamic work environment surrounded by experts and innovators. Additional projects within the Translated AI team include Machine Translation and participation in research endeavors like the Meetween and DataTools4Heart projects. Translated prioritizes diversity and inclusivity, fostering an environment where all individuals are valued and supported to reach their full potential.
Link: https://www.linkedin.com/jobs/view/3913832780/?refId=Y6DczOxfRUCA0I9O2K3wog%3D%3D&trackingId=Y6DczOxfRUCA0I9O2K3wog%3D%3D
Senior Scientist, Foundation models for speech
Translated
he "Senior Scientist, Foundation models for speech" role at Translated focuses on advancing Large-scale Language Models (LLMs) for speech tasks, particularly within the Meetween project. Meetween, a 7M€ collaborative research initiative led by Translated, aims to revolutionize human communication using LLMs and multimodal foundation models. The project encompasses various research areas such as Deep Learning, Machine Translation, and AI Digital Assistants.

Responsibilities include designing deep learning multimodal neural architectures, conducting experiments, monitoring benchmarks, and coordinating with partners. Candidates should possess a completed PhD or four years of industry research experience in deep learning, proficiency in PyTorch, and familiarity with Docker, Unix OS, and GPU experiments. Strong communication skills, experience in speech and language technology, and a track record of relevant scientific publications are required.

The position offers the opportunity to collaborate with leading speech processing teams, utilize ample computing resources, and contribute to open-source initiatives. Translated provides a stimulating work environment at Pi Campus in Rome, alongside perks like gym facilities, regular tech talks, and bonuses for healthy lifestyle choices. The company values diversity and fosters an inclusive culture where all individuals are empowered to excel.
Link: https://translated.applytojob.com/apply/job_20230929140538_K7FHBEFTTEZSDORZ
Senior LLMs Scientist – LLM4EO
Pi School

The "Senior LLMs Scientist – LLM4EO" role at Pi School focuses on advancing Large Language Models (LLMs) for Earth Observation (EO) and Earth Science applications. The project, led by Pi School, aims to develop AI-powered "Digital Assistant" interfaces tailored for EO and derived Earth Science textual information, leveraging NLP and LLMs to enhance communication of scientific knowledge.

Responsibilities include designing deep learning neural architectures, fine-tuning pre-trained LLMs, conducting experiments, monitoring benchmarks, and providing guidance to junior team members. Candidates should possess a PhD or four years of industry research experience in deep learning, proficiency in Python and ML/DL frameworks, familiarity with Docker and Linux, and a track record of relevant scientific publications. Experience in language technology and training/fine-tuning LLMs is required.

The position offers the opportunity to collaborate with leading AI teams, utilize high computing platforms, and contribute to open-source efforts. Pi School provides a dynamic work environment at Pi Campus in Rome, with perks like sports activities, access to the pool, and opportunities for personal projects. The company values diversity and fosters an inclusive culture where everyone is empowered to excel.
Link: https://picampus-school.com/careers/senior-llms-scientist-llm4eo/
Intern and FTE position in foundation models and generative AI
Sony AI
Our team in Sony AI and Sony Research has very limited amount of HC for both FTE and interns in the areas of foundation models and generative AI, especially in vision domain. Locations could be in US(flexible), Tokyo, Zurich or anywhere on earth. Our team currently has 10+ FTEs (all PhDs) from top universities (Harvard,MIT,Princeton ,EPFL,NTU,CUHK,Zhejiang Uni,etc)and had attracted 30+ excellent interns in the past 3 years. Our team had won a long list of awards at top venues,including but not limited to ICML,ACL,CIKM,IEEE,IJCAI,AAAI, WWW, etc. We sincerely welcome highly self-motivated candidates to join us!Feel free to drop me an email lingjuanlvsmile@gmail.com or put an application below:
https://ai.sony/joinus/job-roles/Research-Scientist-Vision-Foundation-Model/

https://ai.sony/joinus/job-roles/Research_Intern_Vision_Foundation_Model/

https://ai.sony/joinus/job-roles/Research_Intern_Privacy-preserving_deep_generative_models/
Link: None
Director/Manager of AI -LLM
GE Healthcare
We are hiring a Director of AI Science – LLM leading the development of LLM solutions within healthcare. This role will report to our VP of AI. As a Director of AI Science, you’ll partner with engineering and business teams, and will be responsible for directing a team of AI scientists and AI engineers to build new LLM solutions as a new AI capability of GE Healthcare and deliver state-of-the-art solutions to internal and external customer’s business and mission problems. Your team will be working with terabytes of text, images, and multimodal patient data to address real-world healthcare challenges. Roles and Responsibilities
- Lead a team of AI scientist and AI engineers to work with large-scale datasets, design and develop novel LLM solutions based on multimodal health data including medical images, electronic medical records, waveforms, and clinical reports.
- Lead the model development lifecycle including model design, experiment, evaluation, prototyping, and production.
- Researching and evaluating emerging technology, industry, and market trends to assist in product development and/or operational support activities.
- Demonstrate strong technical leadership as well as knows how to hire, develop, and retain high quality technical talent.
Required Qualifications
- Graduate degree in computer science or related areas with multi years of industry experiences (PhD preferred).
- 4+ years of science or engineering manager experience.
- Experience in one area of computer science (e.g., Natural Language Understanding, Computer Vision, Machine Learning, Deep Learning, Algorithmic Foundations of Optimization), with publications in NeurIPS, ICML, ICLR, AAAI, KDD, CVPR, EMNLP, ACL.
- Experience with one or more general purpose programming languages (e.g., Python, Java, C/C++, etc.) In depth experience with Spark/Hadoop and either PyTorch/Tensorflow.
- Experience creating production environment data analytics and applications.

Link: None
Principal AI Scientist - Medical Imaging Foundation Models
GE Healthcare
We are looking for highly motivated individuals, passionate about generative AI, medical imaging foundational models, deep phenotyping, precision medicine to join the newly formed GE Healthcare AI group. As a Principal AI Scientist, you will partner with engineering and business teams, and will work with other AI scientists and AI engineers to lead the development of new medical imaging foundation models as a new AI capability of GE Healthcare and deliver state-of-the-art solutions to internal and external customer’s business and mission problems. Your team will be working with terabytes of text, images, and multimodal patient data to address real-world healthcare challenges.Job Description
Responsibilities:
- Working with large-scale and multimodal medical imaging datasets, design and develop novel machine learning algorithms particularly foundation models to support diverse downstream tasks.
- Lead the building of the prototypes to enable development of high-performance AI algorithms in scalable, product-ready code.
- Staying current on published state-of-the-art algorithms and competing technologies.
- Contributing to the development of software and data delivery platforms that are service-oriented with reusable components across teams (multiple teams) that can be orchestrated together into different methods for different businesses.
Basic Qualifications:
- Graduate degree in computer science or related areas with 4+ years of industry experiences (PhD preferred).
- Strong expertise in computer vision with publications in top conferences such as NeurIPS, ICML, ICLR, AAAI, KDD, CVPR, ECCV, ICCV.
- Experience with one or more general purpose programming languages (e.g., Python, Java, C/C++, etc.) In depth experience with Spark/Hadoop and PyTorch/Tensorflow.
- Experience creating production environment data analytics and applications.
- Experience working with large scale AI training, prompt tuning, distillation, robustness, quantization.

Link: None
Member of Technical Staff (LLM and Multimodality)
Boson AI
Join Boson AI, with our founders Dr. Alex Smola and Dr. Mu Li to build next-gen LLMs. We have openings for both scientist and engineer roles in data, modeling, multimodality, evaluation and more. Apply directly through the URL and mention you saw our posting at ICLR!
Link: https://jobs.lever.co/bosonai
AI Scientist/ Senior AI Scientist
GE Healthcare
We are looking for a highly motivated individual, passionate about foundational AI models to join the newly formed GE Healthcare AI group. As the Senior AI Scientist, you will focus on exciting generative vision, text, speech, time-series, and multi-modal problems related to segmentation, object detection, large-scale generative models, large-scale pretraining, prompt tuning, distillation, robustness, responsible AI, quantization, etc.
Additionally, you will be responsible for:
- Developing and implementing novel machine learning algorithms particularly in the area of LLM to provide automation of clinical tasks using one or more of medical images, electronic medical records, waveforms, and clinical reports.
- Demonstrating algorithms to meet accuracy requirements on general subject population through statistical analyses and error estimation.
- Exploring learning from human feedback and assisting humans evaluating AI.
- Building prototypes to enable development of high-performance AI algorithms in scalable, product-ready code.
- Working with large-scale datasets, designing, and developing generative algorithms.
- Staying current on published state-of-the-art algorithms and competing technologies.

Link: None
大模型相关算法研究
Sensetime Research 商汤科技
2024年4月23日,商汤科技SenseTime举办技术交流日活动,正式发布“日日新SenseNova 5.0”大模型体系,其综合能力全面对标GPT-4 Turbo。同时,商汤在业界首次推出“云、边、端”全栈大模型产品矩阵,包括商汤日日新·端侧大模型、端云协同解决方案,以及面向金融、代码、医疗、政务等领域的边缘产品——“商汤企业级大模型一体机”。技术领跑加速生成式AI向产业落地的全面跃迁,实现大模型按需所取。

工作内容:
探索大语言模型算法方向,包括但不限于:多模态大模型,大模型Agent,大模型量化端侧部署,工具调用,长文本处理等。

招聘:
社招、校招、实习生等岗位充足。
Link: None
Machine Learning Engineer - Scaling & Performance Optimization
InstaDeep
InstaDeep is looking to hire a passionate Machine Learning Engineer to join InstaDeep Research. We are looking for people deeply passionate about high performance ML Engineering with real world impact. Our team works on applying state of the art performance methodologies across our research tracks and applied projects in both Bio AI and Decision Making AI allowing us to have wide spread impact across the company. If you are excited about building custom CUDA kernels, SOTA model architectures, Quantisation Fine-Tuning or Distributed Training please reach out to me!
Link: https://www.instadeep.com/job-offer/92900fa3-5501-4506-a63f-cebee958fc6f/
llm engineer, algorithm engineer
modelbest inc
Training SOTA llms, exploring its applications with agents
Link: None
PhD Student
CISPA / SprintML
Introducing the SprintML Lab

We are the SprintML lab with a research focus on Secure, Private, Robust, INterpretable, and Trustworthy Machine Learning. The lab is jointly led by Professors Adam Dziedzic & Franziska Boenisch. We are located at the CISPA Helmholtz Center for Information Security in Saarbrücken, Germany. Get to know our team and find out about our latest research.

Join SprintML!

We are currently hiring Ph.D. students, Postdocs, and Research Interns with a research focus in one or multiple of the following areas:

Secure and Robust Machine Learning
Privacy-Preserving Machine Learning
Distributed and Federated Learning
Machine Learning Model Confidentiality
Trustworthy Language Processing

If you are interested in working with us, please send an email with your CV and research interests to Adam Dziedzic adam.dziedzic@sprintml.com & Franziska Boenisch boenisch@cispa.de. You can also check this blog post: https://sprintml.com/phdlifes/2023-05-30-contact-advisor.html
Link: sprintml.com
Global  Head of Data & AI
Keenfolks
As the Head of Data & AI at KeenFolks, you will lead our efforts in harnessing the power of data and artificial intelligence to drive impactful marketing outcomes for our clients. You will be responsible for developing and executing data-driven strategies, leveraging advanced AI techniques to optimize campaigns, enhance customer experiences, and uncover actionable insights.

Key Responsibilities:
• Develop and implement data-driven marketing strategies to achieve client objectives.
• Lead a team of data scientists, analysts, and AI specialists to drive innovation and excellence in marketing performance.
• Utilize machine learning and AI algorithms to optimize marketing campaigns, targeting, and personalization.
• Collaborate closely with cross-functional teams to integrate data and AI solutions into various marketing channels and platforms.
• Identify opportunities for automation and efficiency improvement through AI-driven processes.
• Stay updated on the latest trends and advancements in data science, AI, and digital marketing to continuously enhance our capabilities and offerings.

Requirements:
• Bachelor's degree in Computer Science, Data Science, Marketing, or related field; advanced degree preferred.
• Proven experience of 10+ years in data-driven marketing roles, with a focus on AI and machine learning.
• Strong leadership skills with the ability to inspire and mentor a team.
• Proficiency in programming languages such as Python, R, or Java, along with experience with data analysis and visualization tools.
• Deep understanding of AI and machine learning concepts, algorithms, and applications in marketing.
• Excellent communication and collaboration skills, with the ability to effectively convey complex technical concepts to non-technical stakeholders.
• Experience working in a digital marketing agency or similar fast-paced environment is a plus.
Link: keenfolks.com
Machine Learning Engineer (m/f/d)
The Stepstone Group GmbH
Founded in 1996, part of the Axel Springer SE group, The Stepstone Group is one of the most successful international digital recruiting businesses. We operate over 54 job boards with over 67 million visits per month and employ over 3,500 people in more than 20 countries. We deliver the best experience to our candidates and the recruiters we work with from small local players to big global brands across the job industry.

Your work:
- You will join the 3 Data Scientists and 2 ML Engineers in our team, and 40+ Data Scientists & Machine Learning Engineers across the organization, to build and improve AI systems for Stepstone. This will include classical machine learning systems for forecasting, scoring and classification, data enrichment pipelines and building blocks to train, evaluate, and serve large language models.
- You will be actively involved in the engineering, design, implementation, and deployment needed to scale the application of our machine learning models. You can take a project from idea to experiment, to prototype, to implementation!
- You will work with our development stack consisting of AWS SageMaker, MLFlow, Terraform, and others, and help evaluating and introducing any new tools and technologies that might help us work more efficiently. 
- You will also actively work on current LLMs, including fine-tuning and productionizing open source models at scale. 
- Together with other Machine Learning Engineers, you will help define and evolve best practices for our community. 
- You will interact with various product owners across the company for defining and understanding their problems from a technical perspective, contributing to and driving efficient formulations and solutions to these problems. 
- You will keep track of the state of the art in MLOps and scalable techniques for machine learning and optimisation, and actively implement them within the group. 
Link: https://jobs.smartrecruiters.com/StepStoneGroup/743999983108680-machine-learning-engineer-m-f-d-
AI Engineering Manager (m/w/d)
The Stepstone Group GmbH
You will work closely together with 2 teams of data scientists & machine learning engineers. You will drive projects to improve the design of existing AI systems (classical ML & LLMs) on AWS and build new solutions. Your team will provide building blocks to train, evaluate, and serve large language models and demonstrate the capabilities of emerging technologies for Stepstone. In this role, you will cooperate with innovation teams across the company. This will allow you to get a deep understanding of different parts of the organisation and allow you to have significant impact with your contributions.

Your tasks: 
- Enable the AI labs team and closely cooperate with data, infrastructure, and platform teams to design and deploy ML-based services using AWS Sagemaker
- Understand current AI products, identify new opportunities, and drive their implementation.
- Design experiments & deployment solutions in the realm of AI systems
- Drive initiatives in the AI Labs teams to advance current ML workflows and software development standards
- Develop talent in the AI labs team through learning & development as well as recruiting.

Qualifications:
- Industry experience in AWS ML services, including AWS Sagemaker
- Experience in working with DevOps, Cloud Operations, ML-engineering teams
- Expertise in driving projects to build enterprise scale ML & LLM solutions
- Ambition to understand, question, & shape our ML-based services
- Nice to have: Experience in projects involving deployment of LLMs at scale. 
Link: https://jobs.smartrecruiters.com/StepStoneGroup/743999983121833-ai-engineering-manager-m-w-d-
Safe Intelligence - lead/senior/junior research engineer - verifiable robustness
safe Intelligence
All levels considered, not just research lead. Informal chats here at ICLR welcome. Just ping me on the app/LinkedIn or email.

====

Safe Intelligence is a venture-backed spin-out from Imperial College London building solutions to formally verify the correctness of ML models and improve their robustness against vulnerabilities.  Our mission is to develop state-of-the-art research and products that make AI safe and secure for society as a whole.

We seek an outstanding research engineering lead who shares our passion for reliable AI to enable ML adoption in society-critical applications, including autonomous transportation, finance, robotics, medical imaging, and edge computing.

As Research Engineering Lead, you will lead and conduct research aligning with the company mission, particularly on ML verification technology and certified learning. Safe Intelligence research engineers regularly share their results with the broader community by publishing in top conferences, and similar contributions will be welcomed. 

Technical Requirements:

Deep learning, verification for machine learning, or certified learning.

Training NNs or DTs.

Programming, including Python, particularly in the context of large codebases. 

Good communication skills.

Ability to collaborate effectively across multiple functional teams.

As a team, we are:

passionate about delivering solutions to make AI safer for customers and society.

deeply technical and constantly in a state of learning.

committed to communicating clearly and efficiently to several audiences, including developers, clients, researchers, partners, and executives.

fearless in getting "hands-on" with technology and execution.

comfortable with ambiguity with a drive for clarity.

honest, straightforward, and caring about each other’s well-being.

Email join@safeintelligence.ai with a CV if interested to discuss. Informal enquiries welcome!
Link: http://SafeIntelligence.ai
Senior Software Engineer - ML Systems / AI Frameworks / Compilers
Recogni
At Recogni we're innovating in the area of efficient, high-performance AI inference chips and systems for all modalities of modern AI. We’re a startup company with headquarters in San Jose, CA, and Munich, Germany; we also have team members working remotely. We’re at the leading edge of advancing the latest research and product improvements for AI inference solutions that will make AI even more useful for compelling new applications.

We’re looking for a skilled software engineer to join our AI SDK team, building a highly flexible Python software development kit to quantize and optimize models for inference on Recogni’s hardware accelerators. You will help architecting this library from ground-up, focusing on the intersection between the compiler and the Python SDK/ML framework. If that matches your experience and interest, we would love to talk!

The Role:
- AI Stack Development for deploying generative AI models to our hardware, focused on deep learning compiler frontend and graph intermediate representation (IR).
- Compiler Synergies, allowing developers to manually optimize algorithms on our hardware.
- Deeply analyze state-of-the-art AI networks and optimize them for our accelerator by implementing hardware-specific kernels.
- Build SW infrastructure around sharding and collectives that lets developers seamlessly deploy large deep learning models for distributed inference.
- Investigate the most recent advances in machine learning, analyze their runtime on our hardware, and contribute to the hardware-software co-design of our next generation.

Qualifications:
- Experience: 4+ years; proficiency in Python and ideally C++.
- ML Frameworks: Experience in ML framework development OR familiarity with export mechanisms, operator sets, and intermediate representations
- Preferred: Experience in ML system optimization, distributed systems, deep learning compilers, hardware accelerator architectures.
Link: https://boards.greenhouse.io/recogni/jobs/7116484002
Post-doctoral researcher in NLP and ML
Amsterdam UMC, University of Amsterdam
We are hiring a post-doctoral researcher in NLP and ML at the Amsterdam UMC, University of Amsterdam. You will join the CaRe-NLP project led by dr. Iacer Calixto and (co-)funded by NWO, which main goal is to develop human-centric and responsible Natural Language Processing (NLP) and Machine Learning (ML) methods with a focus on Dutch and European healthcare applications.

Our main goals include developing and open-sourcing many LLM-based tools, including interpretable and explainable prediction models, models for privacy-preserving synthetic patient EHR data generation, and LLMs with physicians in the loop for more efficient learning with synthetic data. For more information, please check our group's website or send me an email.

Start date: 1 September, 2024 (or earlier if possible).
Link: https://nlp4health-lab.github.io/projects/carenlp_project/
Principal Machine Learning Researcher
Qualcomm Technologies Netherlands B.V.
At Qualcomm AI Research, we are advancing AI to make its core capabilities – perception, reasoning, and action – ubiquitous across devices. Our mission is to make breakthroughs in fundamental AI research and scale them across industries. By bringing together some of the best minds in the field, we’re pushing the boundaries of what’s possible and shaping the future of AI.

As Principal Machine Learning Researcher at Qualcomm, you conduct innovative research in machine learning, deep learning, and AI that advances the state-of-the-art.

· You develop and quickly iterate on innovative research ideas, and prototype and implement them in collaboration with other researchers and engineers.

· You are on top of and actively shaping the latest research in the field and publish papers at top scientific conferences.

· You help define and shape our research vision and planning within and across teams and are passionate at execution.

· You engage with leads and stakeholders across business units on how to translate research progress into business impact.

· You work in one or more of the following research areas: Generative AI, foundation models (LLMs, LVMs), reinforcement learning, neural network efficiency (e.g., quantization, conditional computation, efficient HW), on-device learning and personalization, and foundational AI research.

Working at Qualcomm means being part of a global company (headquartered in San Diego) that fosters a diverse workforce and puts emphasis on the learning opportunities and professional development of its employees. You will work closely with researchers that have published at major conferences, work on campus at the University of Amsterdam, where you have the opportunity to collaborate with academic researchers through university partnerships such as the QUVA lab, and live in a scenic, vibrant city with a healthy work/life balance and a diversity of cultural activities.

Check the link for more information.
Link: https://careers.qualcomm.com/careers?query=3057993
Sr. Machine Learning Engineer for LLM/Multimodal LLM
Apple
Synthetic data generation, data influence, sampling and selection for LLM and Multimodal LLM

https://careers.apple.com/en-us/details/200537887/aiml-sr-machine-learning-engineer-data-and-ml-innovation?team=MLAI
Link: None
Phd/Postdoc Positions
University of Wisconsin Madison
PhD and postdoc positions at the University of Wisconsin Madison, starting next cycle. Projects involve intersection between machine learning and theoretical computer science. Please feel free to email at silwal@mit.edu if interested!
Link: sandeepsilwal.com
Research Scientist / Engineer
AI Safety Institute
We evaluate catastrophic risks from Autonomous AI systems.

Both research scientist and research engineer roles available (at all levels).

Mark yourself as interested and we’ll reach out directly if your profile seems like a good fit for the roles we have.
Link: None
Research Scientist - Machine Learning & Biopharma
SandboxAQ
Leverage and improve state-of-the-art machine learning techniques in Chemistry and Biophysics to accelerate novel drug discoveries
Link: https://www.sandboxaq.com/careers-list?gh_jid=5121519004
Associate Director, Data Science - Imaging and AI Research
Merck
Primary Responsibilities:

• Drive research, design, and development of cutting-edge, high-performing AI/ML algorithms leveraging multimodal medical imaging datasets, particularly foundation models to support diverse downstream tasks.

• Contribute to the development of software and reusable AI/ML capabilities that can be integrated into AI/ML applications.

• Collaborate with cross-functional team to identify research questions, data requirements, and develop appropriate machine learning solutions.

• Stay up to date with the latest advancements in medical image analysis, machine learning, and computer vision, and proactively propose innovative approaches to enhance our capabilities.

• Publish research findings in relevant conferences and journals, and actively contribute to the scientific community through knowledge sharing and collaboration.

Required Experience and Skills:

• PhD in Computer Science, Physics, Electrical Engineering, Biomedical Engineering, or a related field with 4+ years industry experience, MS with 8+ years of experience, or BS with 12+ years of experience.

• Strong background in machine learning, deep learning, generative AI, and computer vision applied to large-scale medical imaging.

• Extensive experience in designing and developing state-of-the-art novel machine learning algorithms particularly foundation models and representation learning to support downstream tasks.

• Demonstrated experience in programming languages such as Python, and experience with deep learning frameworks and libraries like PyTorch.

• Solid understanding of medical imaging modalities, image processing techniques, image segmentation, and image registration.

• Interest in life sciences problems and disease biology, and willing to learn from and teach others.

• Excellent communication skills and ability to work collaboratively in multi-disciplinary team.
Link: https://jobs.merck.com/us/en/job/R289397/Associate-Director-Data-Science-Imaging-and-AI-Research
Machine Learning Scientist / Senior Data Scientist
SES AI
At SES AI, we are at the forefront of revolutionizing lithium-metal battery creation with our groundbreaking approach that integrates cutting-edge machine learning techniques into our research and development processes. Our mission is to lead the next wave of scientific discovery in material science, powered by advanced AI technologies with a dedication to AI for Science.

To learn more about SES, please visit: www.ses.ai

Please contact Kai Liu for more information or review the job posting below. There are multiple openings for the following four directions:

https://www.linkedin.com/jobs/view/3911217188/

https://www.linkedin.com/jobs/view/3911212996/

https://www.linkedin.com/jobs/view/3911219140/

https://www.linkedin.com/jobs/view/3905896749/
Link: www.ses.ai
Research Scientist, Machine Learning and Computational Biology
InstaDeep
InstaDeep is looking for Research Scientists to join our Research Team in London, working at the intersection of machine learning and life sciences. Our in-house Research Team aims to build foundational expertise and develops the next-generation of deep learning technologies for life science applications; for example, generative models for protein sequence and structure, protein structure prediction and inverse folding, ML-enhanced molecular dynamics, learning meaningful representations from proteomics datasets, and more. This necessarily requires expertise not just in machine learning, but also in the curation of experimental data and computational modelling techniques such as homology modelling, molecular dynamics with classical force fields, quantum chemistry calculations with density functional theory.

As a Research Scientist, you will leverage you expertise to help shape and deliver the our research agenda, enabling us to stay ahead of the curve in this exciting field.
Link: https://www.instadeep.com/job-offer/b03e4fa0-7339-4a7e-b1b1-c33b9a756e4e/
Research Engineer, Machine Learning and computational biology
InstaDeep
InstaDeep is looking for Research Engineers to join our Research Team in London, working at the intersection of machine learning and life sciences. Our in-house Research Team aims to build foundational expertise and develops the next-generation in of deep learning technologies for life science applications; for example, generative models for protein sequence and structure, protein structure prediction and inverse folding, ML-enhanced molecular dynamics, learning meaningful representations from proteomics datasets, and more. This necessarily requires expertise not just in machine learning, but also in the curation of experimental data and computational modelling techniques such as homology modelling, molecular dynamics with classical force fields, quantum chemistry calculations with density functional theory.

As a Research Engineer, you will work closely with our Research Scientists to support our ambitious research agenda.
Link: https://www.instadeep.com/job-offer/5ab093cc-e57a-474c-a4b2-0aeef8b85979/
Research Scientist Intern (Search)
Jina AI
Internship with the focus on the search foundation models such as Embeddings, Reranker, Retriever. Open to Undergraduate, Master and PhD students.

Also the CEO Han is at the conf, ping him and say 👋
Link: https://jina.ai
Algorithm Expert & Intern
Ant Group
Looking for candidates (experienced, fresh
graduate, & intern) working on large
models for nlp, code, time series, graph &
multi-modalities (Base in China)
Research Scientist/Engineer
Jina AI
Full-time position with the focus on the search foundation models such as Embeddings, Reranker, Retriever and Prompt Optimizer. Required experience: model tuning, distillation, fine-tuning, fast inference (ggml, kv/attention optimization)

Also the CEO Han is at the conf, ping him and say 👋
Link: https://jina.ai
PhD Positions (Trustworthy ML, Efficient LLM finetuning, Sparse Neural Networks)
University of Calgary
Multiple openings for PhD students in topics such as LLM finetuning, sparse neural network training, trustworthy ML, etc. Exceptional candidates may qualify for scholarship top up to graduate funding.

Calgary is consistently ranked as one of the most livable cities in the world, one of the most affordable cities in Canada to live in, and is located only an hour away from the best part of the Canadian Rocky Mountains.

Please reach out directly: yani.ioannou@ucalgary.ca
Link: https://www.calgaryml.com
Staff Machine Learning Engineer (m/w/d)
The Stepstone Group GmbH
You will work closely together with 2 teams of data scientists & machine learning engineers. You will help us to improve the design of AI systems (classical ML & LLMs) on AWS and to draft and build new solutions. Such solutions include data enrichment pipelines and building blocks to train, evaluate, and serve large language models.

What the role will look like on a day to day basis:
- Work together with the AI labs, Data, Infrastructure, and Platform teams to design and deploy ML-based services using AWS Sagemaker and other cloud based solutions
- Analyse current AWS account setup for data scientists & MLEs and improve it together with StSt MLE & DevOps experts
- Understand current AI pipelines and their integration with other services
- Design & build infrastructure to facilitate experimentation & deployment of AI systems
- Collaborate with the AI Labs teams to advance current ML workflows and software development standards

Qualifications:
- Industry experience in AWS ML services, including AWS Sagemaker
- Experience in DevOps, Cloud Operations, ML-engineering
- Experience in AWS administration and permission management
- Expertise with building enterprise scale ML & LLM solutions
- High proficiency with Docker, IaC (Terraform), CI/CD (Atlassian Bamboo)
- Ambition to understand, question, & shape our ML-based services
- Provide guidance on IaC and CI/CD best practices to increase the efficiency in deployment and management of resources. 
- Good communication skills in English, both written and verbal. 
- Experience with building and or using model management tools (e.g. mlflow)
- Experience with MLOps (model orchestration, updating, etc.)
- Experience with Kafka is a strong plus as some of the pipelines are event-Driven
- Nice to have: Experience with setting up & managing Vector Databases.
- Nice to have: Experience in deploying LLMs at scale. 
Link: https://jobs.smartrecruiters.com/StepStoneGroup/743999985770743-staff-machine-learning-engineer-m-w-d-
PhD Student
INSAIT
INSAIT provides talented individuals the unique opportunity to engage in world-class research with the goal of becoming independent scientists and technology leaders.

Students receive full PhD fellowships at 36,000 € per year and are mentored by world-class researchers, including INSAIT local faculty and affiliated mentors. The duration of the PhD is up to 5 years.
Link: https://insait.ai/phd
Founding Research Scientist
Radiela
The goal of Radiela is to build the necessary AI systems to unlock infinite scientific discovery. We are seeking founding research scientists to join our team with a unique research thesis: solving intelligence by applying AI to physics and physics to AI.

Philosophical thesis
Knowledge creation is the fundamental driving force of human progress. Anything that is not forbidden by the laws of physics is achievable given the right knowledge.

Technological thesis
Our capacity for knowledge creation is ultimately bounded by our total cognitive power. Amplifying human intelligence with AI is essential to the future of science.

Research thesis
Intelligence is in need of explanatory theories like what quantum theory was for physics. The best playground to discover these is applying AI to physics problems.
Link: https://radiela.com
游戏AI强化学习算法研究员
腾讯
岗位职责:
1. 参与腾讯游戏AI的算法研究和应用,包括但不限于强化学习、模仿学习、元学习等,结合游戏场景,提供技术解决方案;
2. 强化学习算法应用效果优化,提高强化学习效率和效果,并结合游戏场景进行应用;
3. 前沿技术的探索,推进强化学习技术在业务场景的应用;

岗位要求:
1. 硕士及以上学历,计算机、应用数学、模式识别、人工智能、统计学等专业;
2. 对机器学习、强化学习、深度学习等算法原理及其在互联网行业的应用有深入的理解和浓厚的兴趣,在NeurIPS、ICML、ICLR、AAAI等顶会发表论文者优先;
3. 基础扎实,编码过关,熟悉常用的算法和数据结构,熟练掌握C/C++、go、Python等至少一门编程语言,具备较强动手和快速学习能力,能够应用TF、PyTorch等主流框架实现模型搭建与算法调优;
4. 对于游戏AI技术研究探索和应用有浓厚兴趣的同学优先;
Link: None
Research Engineer for LLM development and deployment
HiTZ research center, University of the Basque Country
The HiTZ research center of the University of the Basque Country is the premier research center in AI and language technologies in Spain. It is based in San Sebastian, Spain (top 25 five cities according to Forbes). We received substantial funding for the next years in the field of LLMs and low-resource languages. We are strengthening our LLM group with a motivated research engineer. The offer is for a two-year position starting in the following months.
Link: https://hitz.eus
Post-doc position on LLMs for low-resource languages
HiTZ research center, University of the Basque Country
The HiTZ research center of the University of the Basque Country is the premier research center in AI and language technologies in Spain. It is based in San Sebastian, Spain (top 25 five cities according to Forbes). We received substantial funding for the next years in the field of LLMs and low-resource languages. We are strengthening our LLM group with a motivated post-doc. The offer is for a two-year position starting in the following months. We are happy to accommodate to related research interests of the candidate.
Link: https://hitz.eus
Assistant/associate/full professor
MBZUAI
The Machine Learning department at MBZUAI undertakes rigorous, high-impact, and original research. Topics of interest include, but are not limited to, machine learning for large models, trustworthy AI, explainable AI, deep learning, reinforcement learning, optimization, collaborative learning, representation learning, theoretical machine learning, and causality.
We are actively recruiting faculty at the levels of Full Professor, Associate Professor, and Assistant Professor. Applications will be accepted and reviewed on a rolling basis.
Link: https://drive.google.com/file/d/11Wec_f1YgQyF95R0Stj_ia4foGIZN3Gj/view
Foundation model Research Scientist
DeepLife
**Who we are**

DeepLife is a pre-series A startup focused on addressing the urgent need to increase drug discovery reliability by acting on the earliest step, drug target identification. This consists of identifying, a molecular target, such as a protein, that will trigger the transition from disease to healthy cells. With current methods, only 1 target in 10,000 reach the market, leading to a significant loss of time and efforts in the community.

Our approach is to leverage the recent revolution in the omics data, measuring precisely cells activity at large scale, and build foundation models to mimic cell behavior in various contexts and identify the optimal trigger to reverse disease state. 

We offer a research friendly environment, with 90% of the company holding a PhD, with academic collaborations and publications. The team is international and composed of +10 different nationalities. The company is remote first with most of the work is remote and regular events organized in our offices in Paris.


**Job description**

We are looking for an innovative and hands-on deep learning research engineer willing to develop foundation models on biological data and address needs in drug target identification.


As **Foundation model Research Scientist**, you will:

Build foundation models on biological data in collaboration with the computational biology team

Participate to recruit a team of deep learning researchers

Drive research project in drug discovery 

Work with biotech and academic labs

Mentor junior scientists


**Requirements (ranked by importance order)**

PhD/Post-doc in Computer Science with proven expertise by publishing in top best machine learning conferences (NIPS, ICLR, ICML, UAI, CVPR, ...)

Strong machine learning or applied mathematics education

Experience working in large-scale training and foundation models.

Willingness to learn cell biology and have an impact in drug discovery

Apply here --> https://deeplifeai.welcomekit.co/
Link: https://deeplifeai.welcomekit.co/
PhD students (Trustworthy LLMs)
LIP6, Sorbonne Université
2 open positions for PhD:
- Trustworthy LLMs / alignment
- Evaluation of Reasoning in LLMs

The PhD students will be part of TRAIL (Trustworthy and Responsible AI Lab), a joint research lab by Sorbonne Université and AXA.
Link: https://trail.lip6.fr/category/open-position
Postdoctoral Opening in Machine Learning Modeling for Eye Diseases in 2024 Summer at Harvard University
Harvard University
A postdoctoral position is available in Harvard Ophthalmology Artificial Intelligence (AI) Lab (https://ophai.hms.harvard.edu) under the supervision of Dr. Mengyu Wang (https://ophai.hms.harvard.edu/team/dr-wang/) at Schepens Eye Research Institute of Massachusetts Eye and Ear and Harvard Medical School. The start date is flexible, with a preference for candidates capable of starting in August or September 2024. Salary for the postdoctoral fellow will follow the NIH guideline commensurate with years of postdoctoral research experience.

The postdoc will work on developing statistical and machine learning models to improve the diagnosis and prognosis of common eye diseases. The postdoc will have access to abundant resources for education, career development and research both from the Harvard hospital campus and Harvard University campus. More than half of our postdocs secured a faculty position after their time in our lab.

For our data resources, we have about 3 million 2D fundus photos and more than 1 million 3D optical coherence tomography scans. Please check http://ophai.hms.harvard.edu/data for more details. For our GPU resources, we have 22 in-house GPUs in total including 8 80-GB Nvidia H100 GPUs, 10 48-GB Nvidia RTX A6000 GPUs, and 4 Nvidia RTX 6000 GPUs. Please check http://ophai.hms.harvard.edu/computing for more details. Our recent research has been published in ICCV 2023, ICLR 2024, CVPR 2024, IEEE Transactions on Medical Imaging, and Medical Image Analysis. Please check https://github.com/Harvard-Ophthalmology-AI-Lab for more details.

Your application should include:

Curriculum vitae;
Statement of past research accomplishments, carer goal and how this position will help you achieve your goals;
2 representative publications;
Contact information for 3 references;

The application should be sent to Mengyu Wang via email (mengyu_wang at meei.harvard.edu) with subject “Postdoctoral Application in Harvard Ophthalmology AI Lab”.
Link: https://ophai.hms.harvard.edu/news/postdoctoral-opening-in-machine-learning-modeling-for-eye-diseases-in-2024-summer/
PhD / Post-Doc Scholarships at HPI (Potsdam/Berlin, Germany)
Hasso Plattner Institute
For over a decade now, the Hasso Plattner Institute (HPI) has had the #1 ranked computer science program in Germany according to the CHE Ranking, which is the main German academic ranking. Our institute is located right at the border between Berlin (the exciting capital) and Potsdam (a beautiful UNESCO World Heritage city).

We have a bunch of scholarships for candidates seeking a PhD or Post-Doc position on topics related to large language models, vision-language models, and other areas of machine learning, NLP, and computer vision.

Feel free to reach out via e-mail. The application portal will open in July: https://hpi.de/en/research/cooperations-partners/research-schools/scholarships.html
Link: http://deepdata.demelo.org/join/
DL Researcher
Pinely
Pinely is a high-frequency algorithmic trading company that has been in the market for over 15 years. Our HQ is in Amsterdam, and we have several representative offices around the world. We are a tech-savvy proprietary trading firm with data-driven solutions and cutting-edge technologies. We operate as part of the financial markets infrastructure providing liquidity to increase its efficiency. We are seeking a highly motivated and skilled Deep learning Researcher to join our team.

Key Responsibilities:
- Conduct original research in the areas of artificial intelligence, machine learning, and related quantitative fields.
- Develop and experiment with modern deep learning architectures
- Analyze large, unstructured, and noisy datasets to extract meaningful insights.
- Collaborate with leading research labs and academic institutions to foster innovation and exchange knowledge.
- Continually explore new methodologies and technologies to enhance research outcomes.

Requirements:
- A PhD in Computer Science, Electrical Engineering, Mathematics, or a related quantitative discipline (or expectation of such a degree this year)
- Strong background in ML and mathematical statistics.
- Practical experience and a profound understanding of modern DL architectures.
- Proficient programming skills (Python being preferable).
- Published research findings in top-tier journals and conferences.
- Background in analyzing large, unstructured, and noisy datasets.

What we offer:
- Very competitive salary at the upper end of the market, significant bonuses twice a year, and other benefits.
- The team which consists of great minds, such as Kaggle Grandmasters, ACM ICPC World Finalists and published research findings in A* conferences.
- The versatile and reliable infrastructure to support your strategies and innovations and the capability to test ideas daily on a real-time production leaderboard.
Link: https://pinely.com/deep_learning_researcher
Software Engineer, Machine Learning
Twelve Labs
You will be a vital member of the ML Deployment & Operations Team. Your primary role is to build and deploy the machine learning pipeline in our ML Infrastructure while using the foundation models provided by the ML Modeling & Research Team. You will ensure seamless deployment of models end-to-end and implement best MLOps practices to automate the integration, deployment, and training process. A critical KPI for this role is minimizing the time from model training to deployment on our machine learning infrastructure and serving the model as efficiently as possible in terms of latency and throughput. We’re looking for someone who is excited to collaborate across ML Infrastructure, ML Modeling, and Data Team.

You will:
- Be responsible for Model Serving and ModelOps: manage model-related metadata (using the model registry), implement hardware-accelerated optimization for each model engine, and containerize models for efficient serving.
- Construct an ML pipeline that proficiently serves the trained foundation models in our ML Infrastructure.
- Implement best model validation practices by conducting automatic evaluation benchmarking and performing output comparisons.
- Develop an automatic training/finetune pipeline that includes rigorous data and model validation against the baseline model.
Link: https://jobs.lever.co/twelvelabs/ea0a26b8-132a-4367-a6d8-31cd92b89e77
Research Assistant / Postdoc Researcher
Alibaba-NTU Joint Research Institute
Conducting research on LLM and VLM for Southeast Asian languages, especially from a data-centric perspective. Working with Boyang "Albert" Li, Nanyang Associate Professor at Nanyang Technological University.
ML Research Scientist (Video Embedding Model)
Twelve Labs
[주요 업무]
• 트웰브랩스의 영상 검색, QA, 캡셔닝 등의 제품 발전에 필요한 AI 연구 프로젝트 진행 혹은 영상 이해 분야를 Data-centric하게 풀기 위한 AI 연구 프로젝트 진행
• 팀 리드와 논의하여 진행할 AI 연구 프로젝트를 정한 후 해당 프로젝트를 책임감 있고 주도적으로 수행
• 프로젝트 수행에 필요한 데이터 수집 및 라벨링 방법 및 수행 방식에 대한 논의
• 팀 내에서 진행 중인 각 프로젝트에 대해 ML 팀원 간의 정기적인 소통 및 피드백 제공
• 진행 중인 프로젝트에 대해 팀 리드를 포함하여 팀원들과 함께 정기적으로 소통하며 피드백 제공
• 팀이 가장 효율적으로 일할 수 있는 문화 및 필요한 환경에 대한 논의
Link: https://jobs.lever.co/twelvelabs/96a2c0d1-47d2-49ff-aa49-c0a538d8ecd0
Phd/Master students
Dalhousie Applied Machine Learning Research Lab
Mission:

The Dalhousie applied machine learning lab reenvisions large-scale social network and E-commerce from a data-driven decision-making perspective to forge sustainable, smarter, and responsible online information retrieval systems, including large-scale recommendation system, AI assistant systems, and social network-based Disaster & Disturbance Early Warning System etc.

Research Areas:

Machine Learning and Large-scale Data Analysis, Artificial Intelligence (AI), Information Retrieval, Social Media, Recommender Systems, Sequential Forcasting Systems, Auto-pilot System, and other Large-scale ML Applications.

Apply
If you are interested, please read through this webpage for prospective students: https://web.cs.dal.ca/~gaw/prospective/
Link: https://web.cs.dal.ca/~gaw/prospective/
PhD opportunity at ENS Lyon
CNRS, ENS Lyon
We have an funded PhD position at ENS Lyon in France on developing new self-supervised learning techniques for inverse problems, with applications on exo-planet discovery.

ENS Lyon is a top university in France with a great environment of ML researchers.

Please contact me if you are interested in the position!
Link: tachella.github.io
Postdoc position at ENS Lyon
CNRS, ENS Lyon
We have an 1.5 year open postdoc position at ENS Lyon on developing new implicit neural representations for large scale imaging problems.

ENS Lyon is a top university in France with a highly stimulating environment of ML researchers.

Please contact me for more information on this position!
Link: tachella.github.io
postdoc in LLMs for fostering curiosity in children
Inria
Design and evaluation of Large-Language Models (LLMs) based conversational agents for fostering curiosity-driven learning in children

Description of the postdoc project: https://docs.google.com/document/d/1kUNQ0wSHg_uB1bSS358dQq8WmyWdrUJs/edit

Keywords: Curiosity-driven learning, meta-cognition, generative AI, Large Language Models (LLMs), conversational agents, educational technologies, human-computer interaction, artificial intelligence, field experiments, children.

Co-supervision: Pierre-Yves Oudeyer and Hélène Sauzéon (Inria), Edith Law (Univ. Waterloo)

Host: Inria Bordeaux, Flowers project-team (https://flowers.inria.fr), in the context of the CuriousTech associate team between Inria and Univ. Waterloo (https://flowers.inria.fr/curioustech-associate-team)

Location: Inria Bordeaux (with visits to Univ. Waterloo)

Program/funding: DRI Inria

Duration: 12 to 24 months (starting nov. 2024)

How to apply: contact pierre-yves.oudeyer@inria.fr, helene.sauzeon@inria.fr and edithlaw@uwaterloo.ca with CV, letter of motivation and 2 letters of recommendation (this can be sent later), and using the [application] tag in the email object field. In addition, the application has to be submitted on https://jobs.inria.fr/public/classic/fr/offres/2024-07626 before 30th may.
Eligibility: For the candidates who obtained their Ph.D. in the Northern hemisphere, the date of the Ph.D. defense shall be later than September,1 2022; in the Southern hemisphere, later than April,1 2022.
Link: https://docs.google.com/document/d/1kUNQ0wSHg_uB1bSS358dQq8WmyWdrUJs/edit
Senior Software Engineer, Machine Learning
Arcus Inc.
At Arcus, our mission is to advance AI through better data. We believe that data is the ultimate representation of the world and providing ML models with the highest fidelity representations is the most important challenge to solve for AI today. We’re advancing the state of the art in AI by ensuring that every model has the data it needs.

We’re building the comprehensive data platform that enables enterprises to build intelligent AI applications on their structured and unstructured data. From “chat over your data” to multi-modal, reasoning applications – Arcus scales to the complexity of any intelligent AI application. Arcus manages the data workflows needed to make large-scale, complex data useful for LLMs – from ingesting and indexing the data to providing retrieval and evaluation capabilities – Arcus supports even the most complex AI applications.

We’re extremely well-funded and backed by top tier VCs and angel investors who share our mission and we’re based out of our Flatiron office in NYC.

As a Senior Machine Learning Engineer at Arcus, you will push the frontier of our AI capabilities. You will work closely with our CTO, across the engineering team and with our customers to design, build, and productionize intelligent and dynamic AI/ML systems for building LLM applications over complex data. This includes algorithms for representing and indexing structured and unstructured data, understanding and decomposing complex queries, using agent architectures with tool-use to dynamically interact with heterogeneous data, and much more. Our goal is to define the future of Data-Centric Generative AI.
Link: https://www.arcus.co/blog
PhD student
University of Massachusetts Lowell
Looking for motivated, talented folks with solid technical background interested in LLM training dynamics, parameter-efficient methods and model interpretability. Come join the Boston-area academic ecosystem. Please reach out by email or ping me here.
Link: None
Research Scientist / Interns
GenAI Startup
We are GenAi startup based in London and Palo Alto / SF. Team ex Salesforce, Microsoft, University Colledge London, Stanford etc. we are working on AI Agent infrastructure for Knowledge Experts. We have exciting research opportunities/ paper collabs / internships in the following areas

- LLM safety and RAG optimization / Guardrailing systems
- Distributed Learning and Federated Learning
- Multimodal Foundational models

Link: None
Applied Scientist
Amazon
Looking for Machine Learning experts in various areas: Search, NLP, LLM, RecSys, Deep Learning and Reinforcement Learning
Link: None
ML Engineer - Large Language Models
Nous Research
Nous Research builds simulators that are best aligned for the variety of human experience. Our work in LLMs, data synthesis, fine-tuning, output steering, and transformer architecture is done to better reflect the user’s desired world model.

We are dedicated to advancing the field of artificial intelligence. We challenge the assumption that closed technology will forever claim the peaks of innovation, and instead, we offer the people potent open-source research, models and code.

Join us in our quest of reshaping the future of artificial intelligence. Together, we can foster a community where collaboration and transparency reign, where breakthroughs are shared and progress knows no bounds.

You will:
- Implement novel scalable machine learning algorithms for training frontier large language models.
- Collaborate with research teams to define requirements, conduct experiments, and iterate on model training efficiency and performance.
- Optimize novel model training pipelines and infrastructure for efficiency and scalability.
- Incorporate cutting-edge techniques and technologies in natural language processing (NLP) and machine learning.
- Analyze and interpret model behavior to improve performance and robustness.
- Develop and implement monitoring systems to track and analyze training runs of large language models, ensuring stability and efficiency.
- Contribute to the development of open source tools and frameworks for model evaluation, monitoring, and debugging.
Link: https://nousresearch.com/
ML Engineer - GPU Kernels
Nous Research
Nous Research builds simulators that are best aligned for the variety of human experience. Our work in data synthesis, fine-tuning, output steering, and transformer architecture is done to better reflect the user’s desired world compatible language model.

We are dedicated to advancing the field of artificial intelligence. We challenge the assumption that closed technology will forever claim the peaks of innovation, and instead, we offer the people potent open-source research, models and code.

Join us in our quest of reshaping the future of artificial intelligence. Together, we can foster a community where collaboration and transparency reign, where breakthroughs are shared and progress knows no bounds.

You will:
- Develop and optimize GPU kernels (eg. CUDA, Triton) for accelerating machine learning algorithms, focusing on performance and scalability of frontier large language models.
- Collaborate with research teams to understand requirements and implement efficient GPU-accelerated algorithms.
- Iterate on GPU kernel designs to improve efficiency and minimize latency for large-scale model training and inference.
- Implement cutting-edge techniques in GPU programming and machine learning to enhance model performance.
- Analyze and optimize GPU kernel behavior to ensure robustness and stability under various workload conditions.
- Design and implement monitoring systems to track GPU utilization and performance metrics during model training and inference.
- Contribute to the development of open-source GPU-accelerated frameworks and libraries for machine learning and deep learning applications.
Link: https://nousresearch.com/
PhD position Naive Learning of Causal World Models
Sorbonne Université
The proposed thesis seeks to explore the autonomous learning of adaptive world models through
sensorimotor interaction with the environment. The term world model [5] encompasses both the
identification of meaningful latent variables to describe the environment (i.e. finding a disentangled
state representation that separates individual factors of environmental variation), and the prediction of
the evolution of those variables over time in response to the agent’s action (i.e. learning the transition
function of a markov decision process). Such models reflect the agent’s understanding of its
environment and can be utilized in model-based reinforcement learning algorithms to guide its
behavior. Research has indicated that models effectively incorporating the causal structure of the
environment demonstrate enhanced adaptability to distribution shifts, thus improving the adaptability
of robots and intelligent systems [6]. This thesis aims at contributing to the domains of causal
discovery and causal representation learning in the context of developmental robotics. Initial research directions will involve studying the connections between causal [7] and other
disentangled representation learning frameworks [8], and exploring how the agency of intelligent
systems can be leveraged to enhance the learning of world models, for instance through specially
designed intrinsic motivations [9, 10]. The proposed algorithms will be based on artificial neural
networks for function approximation, and validated in simulated environments.
Director- Chemistry AI
Novartis
Chemistry Based AI/ML research group senior leader with the AI & Computational sciences team.
Link: None
Postdocs ML / NLP / Multimodality at U Amsterdam
University of Amsterdam
The University of Amsterdam invites applications for postdoctoral positions on the intersection of ML, NLP, and Computer Vision. The research is funded by NWO (Dutch Science Foundation) grant of Ivan Titov (http://ivan-titov.org/). The postdocs and PhD students will be employed by the University of Amsterdam and will be members of the Institute for Logic, Language, and Computation and the Faculty of Science. The collaboration is envisaged with researchers at the University of Amsterdam (e.g., Efstratios Gavves, and Wilker Aziz), as well as at the University of Edinburgh (e.g., Edoardo Ponti, Hakan Bilen, Sidharth N., Pasquale Minervini and Kenny Smith).

The research will focus primarily on the following directions (or their intersections):

1) Modular and decentralized learning in multimodal settings

2) Learning from language in grounded settings: exploiting knowledge embedded in language and language models to help solve decision-making applications and produce generalizable and interpretable models for these tasks

3) Emergent communication and collaboration: developing agents, which learn to communicate with each other to solve problems, while maintaining transparency to humans and improving with human feedback.

Application deadline: May 31, 2024

For informal enquiries please contact: Ivan Titov (titov@uva.nl)
Ivan is attending ICLR, so please feel free to connect with him for a discussion.




Link: https://www.illc.uva.nl/NewsandEvents/News/Positions/newsitem/14960/Two-Postdoctoral-Positions-in-Machine-Learning-with-NLP-and-Computer-Vision
3 Postdocs University of Edinburgh
University of Edinburgh
Edge AI. LLM planning. Personalisation. 1 postdoc in Each. Happy to discuss more.
2-3 PhD Studentships University of Edinburgh
University of Edinburgh
Working with Amos Storkey. Full funding available for UK/Irish Nationals or permanent residents.

Various topics loosely in the area of Machine Learning Systems.
Any level including doing a Ph.D
Peng Cheng Lab
Information technology at Peng Cheng Laboratory (AI, Telecommunications, Networks)
Link: https://mp.weixin.qq.com/s/A48zqMxgEqI0aL7zmPBO7Q
Research Scientist
harvey.ai
# Why Harvey
Harvey is a secure AI platform for professionals in law, tax, and finance that augments productivity and automates complex workflows. Harvey uses algorithms with reasoning-adept LLMs that have been customized by our expert team of lawyers, engineers and research scientists. Some reasons to join Harvey are:
- Exceptional product market fit: We have partnered with the largest law firms and professional service providers in the world like A&O, PwC, and many others.
- Strategic investors: Raised over $100 million from strategic investors including Sequoia, Kleiner Perkins, and the OpenAI Startup Fund.
- World-class team: Harvey is hiring the best technical and non-technical talent from places like DeepMind, Google Brain, Stripe, FAIR, Tesla Autopilot, Superhuman, and Glean.
- Partnerships: Our engineers and researchers work directly with OpenAI to build the future of generative AI and redefine professional services.
- Performance: $0-20M ARR in the last 12 months.
- Value: Top of market cash and equity compensation.

# Responsibilities
Research Scientists at Harvey wear many hats. In this role, you may work on the following:
- Zero-to-one product development: rapidly prototype, evaluate, and integrate new product features and custom projects for our customers.
- Agent primitives: develop (and continuously improve) best-in-class LLM methods for zero-shot dense retrieval, large-scale hybrid semantic search, recursive abstractive document analysis, etc.
- Agentic workflows: design and implement LLM agents that use these basic primitives and external tools to deliver high-quality, long-form work outputs.
- Evaluation: Create rigorous evaluation protocols combining human preference judgements from domain experts and synthetic data generation.
- Custom models: Fine-tune LLMs and domain-specific embeddings models for knowledge work tasks.
Link: https://jobs.ashbyhq.com/harvey/eb010303-9462-40ed-a13a-0e6fdb099c1b
Research Engineer
harvey.ai
# Why Harvey
Harvey is a secure AI platform for professionals in law, tax, and finance that augments productivity and automates complex workflows. Harvey uses algorithms with reasoning-adept LLMs that have been customized by our expert team of lawyers, engineers and research scientists. Some reasons to join Harvey are:
- Exceptional product market fit: We have partnered with the largest law firms and professional service providers in the world like A&O, PwC, and many others.
- Strategic investors: Raised over $100 million from strategic investors including Sequoia, Kleiner Perkins, and the OpenAI Startup Fund.
- World-class team: Harvey is hiring the best technical and non-technical talent from places like DeepMind, Google Brain, Stripe, FAIR, Tesla Autopilot, Superhuman, and Glean.
- Partnerships: Our engineers and researchers work directly with OpenAI to build the future of generative AI and redefine professional services.
- Performance: $0-20M ARR in the last 12 months.
- Value: Top of market cash and equity compensation.

# Responsibilities
Research Engineers at Harvey wear many hats. In this role, you may work on any/all of the following:
- Zero-to-one product development: rapidly prototype, evaluate, and integrate new product features and custom projects for our customers.
- Agent primitives: develop (and continuously improve) best-in-class LLM methods for zero-shot dense retrieval, large-scale hybrid semantic search, recursive abstractive document analysis, etc.
- Agentic workflows: design and implement LLM agents that use these basic primitives and external tools to deliver high-quality, long-form work outputs.
- Evaluation: Create rigorous evaluation protocols combining human preference judgements from domain experts and synthetic data generation.
- Custom models: Fine-tune LLMs and domain-specific embeddings models for knowledge work tasks.
Link: https://jobs.ashbyhq.com/harvey/b8e71f39-9e4f-4f18-bf34-5b492930874f
Research Scientist
UiPath
Research Scientist @ UiPath
This role is within UiPath’s advanced machine learning research group in London.

We focus on building large multi-modal models that can take action and move us closer to useful general intelligence. We are machine learning researchers and engineers working to solve the hard problem of getting machines to use software like humans do.
To make that happen, we need people who are self-propelled, curious and kind. People who love being part of a fast-moving, fast-thinking and high growth company.

Feel free to contact me if you are interested and have any questions.
Link: https://careers.uipath.com/careers/jobs/8654
Ph.D. positions focusing on Causal Inference with Machine Learning
University of Zurich
We have Ph.D. positions at the University of Zurich focusing on various aspects of causal inference with some focus on epidemiological data. Get in touch with me for more details.
Link: None
Postdocs in Generative Modelling
Technical University of Denmark
We seek a 2-year postdoc in generative modelling at the Technical University of Denmark (Compute). The focus is on advancing and applying advanced generative modelling techniques, including diffusion and score-based modelling, to address complex challenges in physical systems (magnetics). Requires PhD in machine learning, experience in deep generative models, and programming proficiency.
Find Anshuk Uppal or Dennis Ulmer at ICLR to hear more about the lab. Contact Associate Professor Jes Frellsen to hear more about the position.
Multiple roles and levels; scopes include dangerous capabilities evaluation researcher/engineer and AI hardware governance researcher.
RAND Technology and Security Policy Center
Among other things, we build model evaluations to help assess the potential of catastrophic risks from advanced AI systems (especially in the domains of biosecurity and cybersecurity, with a focus on autonomous AI systems), and we conduct policy and technical analysis of AI hardware and the global AI hardware supply chain to inform public policy. Please email us if potentially interested, and then we can share more info or application forms.
Link: https://www.rand.org/global-and-emerging-risks/centers/technology-and-security-policy.html
Phd / Postdoc for machine learning in Sweden
Örebro University
The Adaptive and Interpretable Learning Systems lab at Örebro University is looking for PhD and postdoc researchers in machine learning. We are interested in reinforcement learning (e.g. with priorities / lexicographic / constraints / safety), causal representation learning (e.g. for counterfactual regression and fairness), and models with Gaussian processes. Additionally, we are also interested in learning for robotics.

The positions are part of the Wallenberg AI, Autonomous Systems and Software Program (WASP), Sweden’s largest ever individual research program, and a major national initiative for strategically basic research, education and faculty recruitment. The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish industry. For more information about the research and other activities conducted within WASP please visit: http://wasp-sweden.org/.
Deep Learning Data Algorithm Engineer/Specialist
Horizon Robotics
Job Responsibilities
1. Responsible for perception algorithm R&D and data closed-loop in ADAS, urban/high-speed NOA scenarios, including model truth generation link, dataset construction, data analysis, data mining, data quality inspection, indicator watch list, etc;
2. Master the closed-loop links of data mining, annotation, training, deployment and badcase regression, and continuously optimize them along with business development; master the ability to continuously iterate the model through the data closed-loop;
3. Explore the use of data balance, data distillation and other methods to support the sustainable development of end-side and cloud models, as well as build specific datasets for specific scenarios and algorithm regression evaluation work;
4. Support the development and maintenance of automation links such as model training/regression/evaluation/CICD.
Requirements
1. Master/Doctoral degree or equivalent work experience in computer vision, pattern recognition, machine learning, electronic information, robotics and other related disciplines, with more than 1 year of experience in automated driving.
2. in-depth understanding of data structure, algorithms, code optimization and large-scale data processing and other related knowledge; proficient in C/C++ or Python programming, with experience in automated driving data closure is preferred.
3. Familiar with mainstream deep learning algorithms, proficient in one/multiple domains, including but not limited to target detection, segmentation, tracking, multi-task learning, stereo vision, etc., and mastering more than one deep learning training framework (Pytorch, MXNet, Tensorflow...).
Lidar Deep Learning Algorithm Engineer
Horizon Robotics
Responsibilities
1、Participate in the design, development and optimization of Lidar perception algorithms for autonomous driving, including but not limited to Lidar 3D target detection, segmentation, state estimation and traditional point cloud processing algorithms;
2、Participate in the implementation and optimization of Lidar perceptual algorithms in high-level autonomous driving products;
3、Participate in building and optimizing the closed-loop data link and dataset, developing appropriate model evaluation methods, mining corner cases, and improving the performance of Lidar perception;
4、Participate in the development of cloud-based big models, including but not limited to Transformer big models, multimodal fusion big models, etc., as automatic annotation models, to improve the efficiency of point cloud annotation;
Requirements
1, computer, automation and other majors, master's degree or above, more than 1 year of autopilot, and a deep understanding of lidar imaging principles
2, deep understanding of deep learning, excellent programming skills, familiar with C++ and python
3、Strong sense of responsibility and teamwork spirit
4、Publishing relevant papers in mainstream conferences or journals such as CVPR, AAAI, ICML, TPAMI, IJCV, etc., or achieving excellent results in mainstream benchmarks such as Waymo, NuScenes, KITTI, etc. is preferred.
5、Experience in mass production or large-scale engineering projects is preferred.
Tenure track Assistant Professor in AI+Public Health
National University of Singapore
Hi I am Mornin Feng from School of Public Health National University of Singapore. we are setting up a new center for AI for Public Health, where we plan to recruit a team of young faculties who are passionate about the field too.
Next OpenAI (actually open source) startup - Multimodal
Secret
With colleagues from Meta/DeepMind/Microsoft, we are launching a non-profit dedicated to open-source AI research, and committed to have a massive positive impact in healthcare/ecological transition/developing countries/education.

Not just another entity claiming « benefits for humanity »; our priority is to make a tangible positive impact, prioritizing mission over profit.

Looking for exceptional talent, experienced with LLM, computer vision, multimodal, and meta-learning, and model efficiency (quantization/pruning/more advanced). Most importantly, we’re looking for individuals who are truly dedicated to open source AI research for the greater good (if not, OpenAI is a better fit 😀)

If you are interested, reach out to me on LinkedIn, looking forward to meeting you!
Link: https://www.linkedin.com/in/fporcher?utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=ios_app
Associate Director, Data Science -Graph Neural Networks and AI Researcher
Merck
Primary Responsibilities:
Collaborate with cross-functional team to identify research questions, data requirements, and develop appropriate machine learning solutions.
Apply graph-based techniques to model and analyze complex relationships between biological entities, uncovering disease mechanisms and identifying potential therapeutic targets.
Develop deep learning architectures and algorithms tailored for graph-based data, combining graph convolutional networks (GCNs), cutting-edge methodologies for graph-based representation learning, graph attention networks, and transfer learning to enhance disease biology understanding.
Stay up to date with the latest advancements in Graphical Neural Networks, Knowledge Graphs, and related fields, and apply relevant advancements to improve existing methodologies and models.
Publish research findings in relevant conferences and journals, and actively contribute to the scientific community through knowledge sharing and collaborations.

Required Experience and Skills:
PhD in Computer Science, Applied Math, Physics, or a related field and 3+ years academic medical and/or industry experience.
Strong expertise and experience in machine learning, Graphical Neural Networks (GNNs), knowledge graphs, and graph-based technology and analysis.
Experience and solid understanding of graph representation learning, graph convolutional networks (GCNs), and related methodologies.
Proficiency in programming languages such as Python, and experience with deep learning frameworks and libraries like PyTorch, PyG, etc.
Interest in life sciences problems and disease biology, and willing to learn from and teach others.
Excellent communication skills and ability to work collaboratively in multi-disciplinary team.

Preferred Skills and Experience:
Familiarity with life science data is a plus.
Relevant publications in scientific journals and experience contributing to research communities, including NeurIPS, ICML, ICLR, etc
Link: https://jobs.merck.com/us/en/job/R294554/Associate-Director-Data-Science-Graph-Neural-Network-and-AI-Researcher
Professorship Automated Machine Learning and Optimization
TU Dortmund
Professorship (W1) with W2 tenure track Automated machine learning and optimization
Link: https://wirtschaftsinformatik.de/ausschreibungen/tu-dortmund-w1-t.t.-w2-automated-machine-learning-and-optimization
Postdoc
Brunel University
Intelligent RF sensing for human activity recognition.
AI Engineer Intern, Agents
Occam AI
Link to apply and more details about the role: https://jobs.ashbyhq.com/Occam/a68b756a-2567-4741-a59b-7d77ae3b1825

About Occam AI

We’re on a mission to breathe life into software by giving it action taking abilities. We are leveraging recent advances in generative models, reinforcement learning and symbolic AI, to give software the ability to action complex goals. We envision a world in which software applications become their own autonomous agents, trading information, value and decisions with their users and with each other.
We are building a category defining autonomous agent architecture that’s designed from the ground up for complex, high sensitivity, context dependent enterprise software use cases.
Our team is comprised of industry veterans in applied machine learning research and data platforms, who are former leaders and founders from Meta, Monzo and QuantumBlack, amongst others.

About the Role

As an AI Engineer Intern, you’ll have the opportunity to build a state of the art experience in building generative model architectures. We’ll support you in owning a challenging end-to-end generative model focused problem. If you have a strong bias to action, thrive on ambiguity and desire to own problems end-to-end, we’d love to hear from you.

Please apply at https://jobs.ashbyhq.com/Occam/a68b756a-2567-4741-a59b-7d77ae3b1825
Link: https://jobs.ashbyhq.com/Occam/a68b756a-2567-4741-a59b-7d77ae3b1825
Founding AI Engineer, Agents
Occam AI
Link to apply and more details about the role: https://jobs.ashbyhq.com/Occam/529291c4-6d0b-491e-a502-3d324f221107

About Occam AI

We’re on a mission to breathe life into software by giving it action taking abilities. We are leveraging recent advances in generative models, reinforcement learning and symbolic AI, to give software the ability to action complex goals. We envision a world in which software applications become their own autonomous agents, trading information, value and decisions with their users and with each other.
We are building a category defining autonomous agent architecture that’s designed from the ground up for complex, high sensitivity, context dependent enterprise software use cases.
Our team is comprised of industry veterans in applied machine learning research and data platforms, who are former leaders and founders from Meta, Monzo and QuantumBlack, amongst others.

About the Role

As a Founding AI Engineer, you’ll play a critical role in the development and scaling of our agents infrastructure, going all the way from data ingestion to building state-of-the-art action-taking architectures. If you have a strong bias to action, thrive on ambiguity and desire to own problems end-to-end, we’d love to hear from you.

Please apply at https://jobs.ashbyhq.com/Occam/529291c4-6d0b-491e-a502-3d324f221107
Link: https://jobs.ashbyhq.com/Occam/529291c4-6d0b-491e-a502-3d324f221107
Tenure-Track Positions in Artificial Intelligence Applied to Science, Healthcare, or Society
University of Alberta
The University of Alberta is pursuing an Artificial Intelligence (AI) Cohort Hire initiative to hire 21 faculty members doing AI and Machine Learning (ML) research across a range of disciplines and departments. AI/ML has the potential to transform almost all fields of study within the University and almost all aspects of society outside the University. As part of this AI Cohort Hire we are looking for scholars who are actively pursuing this transformational capacity of AI/ML within their own disciplines. In particular, researchers pursuing AI/ML advances within science, healthcare, robotics and automation, and the impact of these advances on society are priority areas for this AI Cohort Hire. AI/ML impacting other disciplines will also be considered.

The successful candidates must hold a Ph.D. (or equivalent) degree by the appointment date. They are expected to have demonstrated research potential strong enough for a promising nomination as a Canada CIFAR AI Chair, typically evidenced by publications in top venues (conferences or journals) within their field. Their research accomplishments should clearly include fundamental advances in AI/ML or fundamental advances in how AI/ML is applied within their discipline. They should also have strong communication skills and demonstrated commitment to highly effective graduate and undergraduate teaching. They will be expected to establish their own funded research programs, supervise graduate students, and teach graduate and undergraduate courses as expected by their home department.

See link for full description.
Link: https://apps.ualberta.ca/careers/posting/908
Research Scientist - AI in psychiatry
Cephalgo
The ideal candidate's favorite words are learning, data, scale, and agility.
Responsibilities
Collect, process, and clean data from diverse sources to prepare it for analysis, ensuring consistency and reliability
Analyze raw data: assessing quality, cleansing, structuring for downstream processing and applying ML and DL techniques
Focus on quantitative analytics and data modeling
Design accurate and scalable prediction algorithms
Ensure scalable ML/DL pipeline construction
Implement data storage solutions optimized for volume, velocity, and variety of EEG data
Collaborate with the team to bring analytical prototypes to production
Stay up-to-date with the latest technologies and trends in data science and machine learning
Qualifications
Master’s degree or equivalent experience in Computer Science
At least 2 years of experience in DL, quantitative analytics, and data modeling
Strong statistical and programming background
Experience in MLOP pipeline construction and big data technologies like Spark, MLFlow, Snowflake, Hadoop
Deep understanding of predictive modeling, machine learning, clustering and classification techniques, and algorithms
Fluency in a programming language (Python, C, C++, Java, SQL)
Excellent problem-solving skills and ability to work independently or as part of a team
Experience in interdisciplinary tasks
We Offer
Competitive salary and benefits package
A collaborative work environment with a supportive team
Opportunities for professional growth and development
Access to the latest tools and technologies
Flexible working hours and remote work options
CEPHALGO focuses on introducing technological innovations to assist medical professionals in providing better mental health care. Located in Strasbourg and extending beyond Europe, CEPHALGO’s patient monitoring technique using EEG and AI is applied in psychiatry across Europe.
Link: https://cephalgo.com
Postdoctoral Researcher, Foundation Models for Human-Aware Interactions and Learning
Toyota Research Institute
Please find full job description at https://jobs.lever.co/tri/7104e850-22b0-49fd-ab48-10aa20f6dd93

If you are interested please apply directly using the link above.
Link: https://jobs.lever.co/tri/7104e850-22b0-49fd-ab48-10aa20f6dd93
NLP Engineer
niklaus.ai
What is it about?
- Training/finetuning LLMs on legal data
- Literature search in NLP
- Building RAG systems

Perks:
- Flexible working hours
- Remote work possible
- Opportunity to learn more about cutting edge open-source NLP

Requirements:
- Reliability, dependability, proactivity
- Good coding skills in Python
- Familiarity with huggingface transformers
- Experience finetuning LLMs
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