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Data Scientist - Machine Learning
We are in search of a talented Machine Learning Scientist | Data Scientist to join the team. In this role, you will be working closely with our entire team of scientists to develop machine learning methods for evaluating chemical structures and predicting new structures that act upon dysregulated protein aggregates that cause neurodegenerative diseases. You must excel in asking the right questions, and applying the right statistical and machine learning methods, to ensure that we are making the right inferences from our biological data. You have a strong understanding of deep learning methods, and can guide our leadership team on when it is appropriate to use such methods vs. more traditional machine learning methods. You treat machine learning/data science as a true science, including writing up your conclusions in Jupyter notebooks or the like to discuss your findings with other team members, including benchlab scientists. You have experience working with the scale and quality of data found in chemistry and biology labs (i.e. not massive text libraries culled from the internet.) You enjoy a mix of practical and theoretical work, and are driven by the impact your work has on concrete decision-making to ensure we meet our long-term goals of getting drugs into the hands of patients with neurodegenerative diseases.
Machine Learning Engineer[All Levels]
Introducing JP Morgan Chase Personalization & Insights Team!


Ever wondered how Chase Travels makes those amazing recommendations? Browsed through the chase app and discovered offers that you never knew existed ? Ever missed the right opportunity to use those hard-earned reward points ? Yearning for insights into what others are using and thinking? Do you want to enhance and perfect all these experiences ?


Are you ready to revolutionize the customer experience? Join our team and make a difference! We're hiring individuals with expertise in reinforcement learning, recommendation systems, Large Language Models, and graph learning. Please reach out to me if you'd like to connect while at the conference to know more about this role. Or email your resumes to !
Engineering Manager, Personalization ML
About the Team
DoorDash is looking for an Engineering Manager with ML background to lead the Personalization engineering team. This team is responsible for building ML ranking and recommendation systems to maximize the value for consumers, merchants and Doordash.

Our Personalization team is a part of our Core Consumer org which owns the top of the conversion funnel from the initial landing page all the way to checkout across iOS, Android, and Web platforms. Personalization is at the center of the Discovery team’s mission. As Doordash expands into new verticals like Grocery, the challenge of helping consumers easily find what they want grows exponentially, so the opportunity is massive!

About the Role
You will lead a team of world-class ML engineers redefining personalized discovery experience through cutting edge ranking and recommendation strategies.

You’re excited about this opportunity because you will…
Lead and grow a team of exceptional machine learning engineers delivering end-to-end ML solutions
Work with Product, Design, and Business stakeholders directly across DoorDash to define the roadmap and vision for the team and deliver immense impact
Encourage innovation, implementation of cutting-edge technologies, outside-of-the-box thinking and teamwork
Build an outstanding team by coaching and empowering engineers through delegation, and applying your technical expertise to hold your team to the highest engineering standards
Scale the team by developing internal, and attracting top external talent
We’re excited about you because…
B.S., M.S., or PhD. in Computer Science or equivalent
7+ years of industry experience
Minimum of 2 years of leadership experience
Broad knowledge of machine learning with strong ML modeling foundation
Extensive experience in building user-facing product and working directly with product managers
Strong communication skills and the ability to partner with teams spanning many disciplines
Applied Statistician
We are looking for experienced data scientists to support the efforts to measure and improve Data Quality of multiple products within Bloomberg. This involves performing sampling design for accuracy measurement, development of anomaly detection models, root cause analysis, timeseries forecasting, among others. This work does not involve language models.

Please apply through Bloomberg’s original job posting.

Position requires 3 days/week in office. You may choose between working out of the New York City (US) or London (UK) offices.
Post Doc
Carnegie Mellon University
We have an open postdoctoral position on spatiotemporal data modeling, anomaly detection, and graph neural networks. See details and how-to-apply at the LINK provided below.
Assistant professor
Institute of computing and technology,Chinese academy and sciences
The research interests are about Graph Neural Networks,Social computing and Large language models
Link: None
Team Lead Trustworthy LLMs
Fraunhofer IAIS / Lamarr Institute
Lead our research on Trustworthy LLMs towards real-world software and solutions that make AI safer. Boost your career at the intersection of research and business.
Assistant / Associate Professor in Financial Analytics
Western University
For the full job post, please follow this link:

**If you want to talk about the position, I'll be all day at the Machine Learning in Finance Workshop on Monday**

The Department of Statistical and Actuarial Sciences, in the School of Mathematical and Statistical Sciences, Faculty of Science at Western University is pleased to announce a search for a probationary (tenure-track) position in Financial Analytics at the rank of Assistant or Associate Professor. The rank and salary will be commensurate with the successful applicant’s qualifications and experience. In exceptional cases, the position may be tenured at the Associate Professor rank. The starting date will be July 1, 2024, or as negotiated.

By November 15, 2023, candidates should submit a curriculum vitae, one-page teaching statement, one-page statement listing experience or interest in professional and/or leadership programs, two-page research plan, and up to three of their most representative publications. Three letters of reference, at least one of which includes detailed comments on the candidate's teaching abilities, will be required for shortlisted applicants. Thus, contact details of at least three referees should be provided along with the rest of the application package to the address below:

Kristina Sendova, Chair
Department of Statistical and Actuarial Sciences The University of Western Ontario
London, Ontario N6A 5B7, Canada

Consideration of applications will begin on November 15, 2023 and will continue until the position is filled. We thank all applicants for their interest, but only those selected for an interview will be contacted.
AI Technical Lead
What you will do:

Work directly with the tech leaders of our portfolio companies to identify opportunities for integrating AI capabilities into their core products and collaborate with their scientists to accelerate development.
Apply the latest research to real-world problems, push the state of the art forward, and publish papers at top conferences.
Work closely with engineers on the integration and deployment of models in production.
Advise startups on how to translate product requirements, formulate problems, and apply best practices and techniques to develop, test, and monitor models.
Communicate effectively with stakeholders to understand requirements and explain complex AI concepts.
Ensure that AI systems are implemented in a responsible, ethical, and unbiased manner.
What you will bring:

5+ years of hands-on experience in the software industry, preferably with growth-stage startups, building ML products end-to-end.
Proficiency in Python and familiarity with packages such as Scikit-learn, Tensorflow, and PyTorch.
Deep understanding of statistical methods and deep learning techniques and their applications in time-series processing, NLP, and computer vision.
Strong software development experience.
Strong mathematical skills, particularly in linear algebra and statistics.
Ability to formulate an applied research problem, design, experiment, implement and communicate solutions with people with different backgrounds.
Ph.D. or master’s degree in Computer Science, Electrical Engineering, Statistics, or a related quantitative discipline with a focus on machine learning, optimization theory, or related areas.
Curiosity and a strong willingness to learn and adapt in a rapidly evolving field.
Senior/Staff ML Engineer in Meta (Ads)
TLDR: We are the central applied ML org at Meta productionalizing SOTA ML models to improve ads ranking across the company. Feel free to connect via this app or on Linkedin. Please do not email your resume over, apply through the links below thanks.

We are the Monetization AI and Ranking Foundation org, previously known as Ads Core ML. We are a dynamic team of highly skilled machine learning researchers and software engineers who are passionate about pushing the boundaries of Artificial Intelligence in the digital advertising industry with a focus on Ads Ranking. Our organization plays a pivotal role in developing cutting-edge capabilities that power the ranking of ads, ensuring they are tailored to the individual users. By constantly enhancing the relevance and recommendation systems for ads on Meta's platforms, our efforts have an important impact, amounting to increased revenue every year. We generate revenue for the company, enabling it to build even better services that foster meaningful connections across the globe.

Senior MLE:

Staff MLE:
Data Engineer
You will be:

Creating and managing ETL jobs to integrate various data sources into our data warehouse.
Creating data models, data marts and dashboards to support various use cases.
Creating data dictionaries and monitoring data quality.
Identifying, designing, and implementing process improvements: automate manual processes, optimize data delivery, improve data reliability, efficiency, and quality, etc.
Maintaining and optimizing the current data infrastructure
Working on GCP with some great tools and tech: Stitch, Airflow, Docker, Terraform, Bigquery, dbt, Tableau; with options to add/improve upon this tooling as needed.
What you will bring:

Strong experience in data modelling and management
Strong experience working with data warehouse, data lake and ETL process.
Strong software development skills in Python.
Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets
Hands-on experience with dbt, Airflow, Docker and BigQuery.
Hands-on experience in developing CI/CD pipelines using tools such as Jenkins, Terraform, Ansible, or Chef.
Strong written and spoken communication skills.

Nice to have:
Experience with applied Machine Learning techniques
Motivation to work in not just the traditional data engineering role, but also support others in analytics and data decision making.
Multiple Postdoctoral positions in AI institute at Stony Brook University
Stony Brook University
Multiple Positions as Empire Innovation Postdoctoral Scholars in the AI Institute at Stony Brook University

Job type: Postdoctoral Fellow or Scholar Location: Stony Brook, New York Expires on: August 31, 2023

Seeded by a $3 million SUNY Empire Innovation Program grant and donor funding, the Institute for AI-Driven Discovery and Innovation (IAI-DDI) at Stony Brook University invites applicants for multiple positions as Empire Innovation Postdoctoral Scholars. Fellowship positions will be associated with research groups associated with Institute faculty, in areas such as:
● Machine Learning and Computer Vision,
● Natural Language Processing and Data Science
● Biomedical Informatics and Computational Neuroscience
● Knowledge Extraction and Formal Reasoning
Applicants should hold a PhD in Computer Science or related discipline and must demonstrate research accomplishments and potential. Candidates seeking to bridge multiple disciplines or bring AI into new scientific domains are particularly encouraged to apply. We have a broad notion of “related discipline”, and will consider outstanding candidates looking to transition into artificial intelligence or machine learning from other fields. We will process applications on an ongoing basis until all positions are filled. The start date is negotiable, but can be as early as Fall 2023. Beyond research, fellows will have modest service duties to expand the missions of the AI Institute.
Home to many highly ranked graduate research programs, Stony Brook University is located 50 miles from New York City on Long Island’s scenic North Shore. Stony Brook University is a member of the prestigious Association of American Universities (AAU) and co-manager of nearby Brookhaven National Laboratory (BNL).

Applications Instructions: Interested applicants should send their vita, cover letter, and list of references to

Stony Brook University/SUNY is an affirmative action, equal opportunity educator and employer.
Link: None
PhD positions at Univ of Michigan CSE
Univ of Michigan
I’m a new assistant prof. of CSE at the Univ. of Michigan—Ann Arbor and my group has several PhD positions available. If you are interested, please don’t hesitate to reach out!

ML topics:
spatiotemporal ML, AI for science, differentiable simulators, time series, uncertainty quantification

public health, community resilience (critical infrastructure networks)

More details:
MLE roles at Instagram Monetization
Meta / Instagram
We are looking for talented ML and System Engineers (IC4/5/6) to innovate the next generation advertising ecosystems at Instagram.

AI-powered Ads creative generation
Media content understanding
User real-time intent modeling
E2E product optimization and ranking

Drop me a message if you are interested.
Link: gnavvy
Research Associate and Postdoc Fellowship
University of Pennsylvania
The University of Pennsylvania Perelman School of Medicine seeks candidates for research associates and postdoc fellow positions. The main focus of these positions is on the development of AI based biomedical data analysis algorithms with an emphasis on advanced machine learning (deep learning) methods for medical imaging data analysis. Responsibilities include involvement in various imaging studies of Alzheimer’s disease, aging, brain development, and neuropsychiatric disorders and supervision of junior research investigators for developing algorithms of image segmentation and registration, time-series data modeling, and pattern recognition. The research will be conducted at the Research Laboratory for Machine Learning and Biomedical Data Analytics of the Center for Biomedical Image Computing and Analytics (CBICA), a dynamically growing medical image computing center, involving several laboratories and many collaborators from diverse fields. The position will provide opportunities to participate in collaborative research projects with multidisciplinary research teams of Penn Medicine and the Children’s Hospital of Philadelphia, as well as to launch an independent research career in the area of computational medical imaging analytics.

University Overview: The University of Pennsylvania, the largest private employer in Philadelphia, is a world-renowned leader in education, research, and innovation. This historic, Ivy League school consistently ranks among the top 10 universities in the annual U.S. News & World Report survey. The University offers a competitive benefits package that includes excellent healthcare and tuition benefits for employees and their families, generous retirement benefits, a wide variety of professional development opportunities, supportive work and family benefits, a wealth of health and wellness programs and resources, and much more.
Data Scientist, Pricing
At Lyft, our mission is to improve people’s lives with the world’s best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft work in dynamic environments, where we embrace moving quickly to build the world’s best transportation. We take on a variety of problems ranging from shaping long-term business strategy with data, making short-term critical decisions, and building algorithms/models/tools that power our internal and external products.

We are looking for a Data Scientist to join the Pricing vertical of the Marketplace team. Pricing is at the core of Lyft’s business, right at the crossroad between technical challenges and business impact. You will be working with a strong data science team who use a variety of models that apply causal inference, economic modeling, Reinforcement Learning and more to the problem of setting prices across multiple Offerings, different regions and time horizons. You will be par tof the cross-functional team to help develop the vision, set roadmaps, and lead execution for future projects in Pricing.

Advanced degree in a quantitative field like statistics, economics, computer science, operations research,; or relevant work experience
4+ years of hands-on industry experience in causal inference or data science
Track record of using statistics, economic modeling and Machine Learning and guiding teams through unstructured technical problems to deliver business impact
Link: None
Business and Marketing Data Scientist, Applied Machine Learning

Build efficient and scalable ML models that help small and midsize businesses around the world to grow their business leveraging the power of Google solutions.

Solve real-world problems with the latest research in deep learning, natural language processing, and understanding.

Work with product teams to understand their objectives, product requirements, constraints, and key metrics.

Propose, build, evaluate and debug machine learning models and algorithms.
Integrate pipelines, models, and predictions into production serving systems.

Senior Machine Learning Engineer
Our business is growing fast, as a key member of our dynamic Digital team, the Machine Learning Engineer will play a critical role in transforming healthcare and combating obesity, one of the most pressing global health challenges. You will harness the power of machine learning to improve provider decision-making processes and to innovate our patient care platformtransform patient experiences, particularly through the automation of patient care.

In addition to building ML models, you will craft production-level back-end APIs and systems. You will be responsible for initiating and leading new projects. This is an opportunity to propel your career, make a significant societal impact, and be part of a passionate team committed to transforming lives.

This role is remote from anywhere within

What we are looking for

Degree in a computational discipline (Computer Science, Electrical Engineering, Information systems, Physics, Computational biology, etc.)
Strong interpersonal and communication skills
Deep knowledge of machine learning, generative AI, and chatbots
Strong understanding of probability theory, statistics and information theory
2+ years work experience (with PhD), 4+ years work experience (with bachelors or masters) building and deploying ML models in production
5+ years experience computer programing with experience with both interpreted (Python, R) and compiled (C++, Java) programming languages
Familiarity with SQL or similar languages
Strong data manipulation and data pipelines and system administration skills
Has experience designing and standing up APIs and services.

PhD positions
Gwangju Institute of Science and Technology
We have multiple openings for MS/PhD position at GIST AI. My group challenges problems that humans can easily solve, but AI has not yet performed well (Abstraction Reasoning Corpus, Rich Math Problems). Please check the link below and send me your updated CV to Sundong Kim: I will follow up with the qualified candidates with further information via email. Also, feel free to hit me up during the conference!
Staff MLE, Search Relevance
You will be responsible for leading the machine learning strategy and projects in Pinterest search, including indexing and document ranking, query and content understanding, personalization, ML based retrieval, shopping, videos, as well as infrastructure efficiency and scalability. In addition, the candidate will work on innovative applications of NLP and other techniques to drive query recommendations, autocompletions, and query based module generation and ranking.
Machine Learning Engineer, Home Relevence & Ranking
The Homefeed Relevance team’s mission is to recommend inspiring & engaging pins for all our Pinners. We are looking for a Tech Lead Architect who can drive cross-team engineering efforts for shipping ML-driven product experiences to our Pinners. You’ll have the opportunity to work on various innovative projects of new product experiences, build large-scale low-latency systems and state-of-the-art machine learning models, and deliver great impact to our Pinners and business metrics.
Staff MLE, Ads Measurement
The Ads Measurement Modeling team provides ML-based solutions for maintaining conversion visibility in today’s privacy sensitive environment. The team is at the forefront of ensuring the continued success of Pinterest’s performance advertising business and is focused on building novel, 0 to 1 solutions for the problems in the area.
Sr. Staff MLE, Ads Product Architect, Monetization
Pinterest is one of the fastest growing online ad platforms, and Advertiser Solutions Group (ASG) is building advertiser products by applying the ML technologies to improve performance and drive value for the advertisers. ASG particularly focuses on product innovation and improvement, and connects all the advertiser products across the entire advertiser lifecycle.
Sr. Staff Data Scientist - Core Ecosystems
We are looking for a Senior Staff Data Scientist for Ecosystem. You will shape the future of people-facing and business-facing products we build at Pinterest. Your expertise in quantitative modeling, experimentation and algorithms will be utilized to solve some of the most complex engineering challenges at the company. You will collaborate on a wide array of product and business problems with a diverse set of cross-functional partners across Product, Engineering, Design, Research, Product Analytics, Data Engineering and others. The results of your work will influence and uplevel our product development teams while introducing greater scientific rigor into the real world products serving hundreds of millions of pinners, creators, advertisers and merchants around the world.
Staff Data Scientist - Ads Market Design
The Ads Marketplace at Pinterest not only connects advertisers with the right audience at the right time, but also fosters innovation and a community of practitioners and researchers working on ads targeting, ranking, and marketplace design. As we continue to innovate and improve ads marketplace efficiency, we are seeking a staff data scientist to improve end to end ads delivery funnel efficiency through market design. You will partner with economists and MLE to tackle the challenging business and technical problems in the market space, all the while helping Pinners make their lives better in the positive corner of the internet.

Staff Marketplace Engineer & Economist
In this role, you will be responsible for developing and executing a vision for the evolution of the Pinterest marketplace. You will design and implement systems that improve the ads delivery funnel, experiments that shape the utility function, auction mechanism design, ad allocation and for deriving new insights through analysis of the marketplace dynamics. In short, this is a unique position, where you’ll get the freedom to work to bring together pinners and partners in this unique marketplace.
Machine Learning Engineer (all levels)- Recommendation
TikTok Core Recommendation Algorithm Teams is hiring for all levels of Machine Learning Engineers. Please see link below for more information.
Machine Learning Engineer (MLE) in Meta Ads Core ML
Meta Platforms
Ads Ranking & Codesign team is a cross functional team with ML engineers and researchers responsible for generating multi-billions of incremental revenue through improving scalability, efficiency and latency of Meta’s most complex and revenue critical Ads models. You will have the opportunity to work on the largest ranking models in Meta Ads with cutting edged modeling research and development.
The team also closely works with infra partners, production owners to develop SOTA algorithms within capacity constraints as well as co-design training/serving systems with new generations hardwares.
The team doesn’t require prior model training/serving experience, just generalists interested in working in the space.

Drop us a message or email if you are interested.
Link: None
Research Engineer - Advertising
Yahoo is a global media and tech company that connects people to their passions. We reach nearly 1B people around the world, bringing them closer to what they love.
The Yahoo Research team within Yahoo Ads Data and Common Services organization is looking for outstanding research engineers. Ideal candidates must have a strong foundation and excellent implementation skills in machine learning/data science. The candidates will have the opportunity to conduct research and implement ML algorithms alongside top scientists/engineers using web-scale data, to make a substantial positive impact on our company and our customers, as well as to potentially contribute to the scientific and open source communities in AI/ML and related areas.

Work with scientists, engineers, and PMs, dive deep into web-scale data to understand the problem; formulate and implement solutions; design experiments and metrics; document and communicate the findings.
Work closely with the engineering partners to push research prototypes into production.
Provide thought leadership to guide the direction of products and services
Review state-of-the-art approaches, explore new ones, propose appropriate solutions, publish at top-tier conferences.

Required Skills:
- Masters/PhD in Applied ML, Data Science, Computer Science, Statistics, Electrical Engineering, Applied Math, or related fields
- Expertise in ML, NLP, web mining, or related fields
- Strong algorithmic problem solving skills
- Expertise in Java, Python, SQL
- Strong communication, presentation, collaboration and interpersonal skills.
- Ability to work remotely and independently across multiple time zones .

Desired Skills:
- Experience with tools like Spacy, Numpy, Pandas, Scikit-learn etc.
- Experience with TensorFlow, PyTorch, LLMs, GenAI, etc.
- Knowledge of big data tools like Hadoop, Apache Spark etc.
- Experience in AWS managed services for ML
- Prior experience doing research, documented through publications
Link: None
Data/ML Engineer Co-op intern
We are overjoyed to be recognized as one of Deloitte’s top 500 fastest-growing technology companies in the US! But wait, there’s even more excitement in store! Get ready for an incredible new journey as we proudly announce our official public listing ALUR. This momentous milestone opens up a new era filled with boundless possibilities and remarkable growth for our company!

At Allurion, our core values of Audacity, Grit, Authenticity, Accountability, and being Data Driven, combined with our passion for innovation, have fueled our growth and will help us achieve our ambitious mission – ending obesity! As part of a recognized Great Place to Work ® in the US, UK, France, Allurions engage as a collaborative global team while solutioning a critical healthcare challenge which affects millions.

What will you be doing?

The Data and Machine Learning Co-Op Intern will join us full time this fall on a semester contract, aiding in the development and refinement of our platform. You will assist in the development and refinement of machine learning algorithms that drive innovation in our virtual care suite. Other responsibilities include: Supporting in data pipelines, training and deploying machine learning models, plus contributing to designing and implementing production-level backend APIs and systems.

What we’re looking for in you:

Pursuit of a degree in a computational discipline
(Computer Science, Electrical Engineering, Information systems, etc.)
Strong interpersonal and communication skills.
Exposure to machine learning, AI, and chatbots.
Basic understanding of probability theory, statistics, and information theory.
Familiarity with both interpreted (Python, R) and compiled (C++, Java)
programming languages.
Experience with SQL or similar languages.



40 Hours per week aligned with your educational institution’s requirements
Staff Machine Learning Engineer
Sony PlayStation
The successful MLOPS Engineer we are seeking will join our team to work on cutting-edge projects such as Emotional Voice Synthesis. In this role, they will take on the responsibility of developing and maintaining machine learning pipelines, deploying models to production, and monitoring their performance. Collaborating closely with data scientists and software engineers, the engineer will ensure seamless integration of machine learning models into our applications. The ideal candidate should possess a deep understanding of machine learning concepts, hands-on experience with cloud computing and deployment, and exceptional communication skills.
Graduate intern Cash App research
Cash App
We have multiple intern opportunities available for graduate students. Positions are remote. You will have the opportunity to do cutting edge work on topics related to fraud and recomender systems. We are interested in time series analysis, graphs, semi-supervised learning, and anomaly detection.
CTO Audio AI startup (co-founder)
Stealth Start-up
Driven engineer with experience building recommender systems open to work on multimodal ones (text/audio)

MLOps experience and a desire to change/drive how AI and humans engage through voice preferred :)
Machine Learning Engineer
Minion AI is on a mission to build a useful web agent. We are the forefront of personalized agents that perform tasks on the web for you. Join us to work on long-term memory, reliability, planning, reasoning, actions, and embodied AI.

We are a small team with prior experience leading Github Copilot, contributing to Apple Vision Pro R&D, and building Twitter ads.

You will actively contribute to the development of AI models: model architectures, data curation, training and inference infrastructure, evaluation protocols, alignment and RLHF, and many other exciting topics.

Degree in Computer Science or related field: with a specialization in Machine Learning, Artificial Intelligence, or related areas.
Experience: 3 years or more experience in research or applied machine learning, deep learning. No prior large model training/inference experience is required, but is considered a plus.
Skills: Proficiency in Python, PyTorch, Transformers and other frameworks.
Mindset: Passionate about AI agents. Team player with a positive attitude and an ability to work in a fast-paced startup environment.

What We Offer:
Competitive Salary & Benefits: Attractive compensation package with equity options. Medical, dental and vision plans for employees.
Growth Opportunities and Impact: Ample opportunities for personal and professional growth in a fast growing startup with ability to impact the future of AI agents and web.

How to Apply:
Please send your resume, cover letter, and any relevant work samples to
Link: None
L5+ ML / Gen-AI Engineer

Handshake is hiring senior, Staff, Senior Staff, and Principal Machine Learning Engineers with a focus on Generative AI reporting to the Vice President of Engineering of the Data organization.

AI is the future and we are excited to invest in providing AI resources for our users on our platform. Is it possible to thoughtfully design a responsible, Generative AI-driven product, that can help our students progress from educational aspirations to career achievements? In this role, you will work on tackling that goal as part of a lean, high-visibility team. You will be responsible for helping advance our AI product and infrastructure vision towards our mission of democratizing opportunity for millions of students on Handshake.

MS/Ph.D. in Machine Learning, Statistics or a related field
7+ years of industry experience.
Experience with modern Machine Learning, Natural Language Processing and Text-mining technologies.
Experience with large-scale distributed systems, server-side engineering, and ML applications in consumer products.
Experience using analytics/ML tools such as Python, R, Spark, BigQuery SQL, or Snowflake.
Experience in any of Golang, Java, Python, or Ruby.
Experience with distributed computing frameworks such as Hadoop or Spark, or distributed training of Machine Learning models.
Experience building applications atop of IAAS (Google Cloud Platform, Amazon Web Services, Azure Cloud Services, etc.)
Experience in optimizing multi-sided marketplaces using ML algorithms.
Experience working directly with cross-functional teams such as product management, analytics, engineering, and design.
Excellent communication skills — ability to succinctly communicate results and tell compelling stories with data to an out-of-domain audience (e.g. presenting findings and deep-dives to senior leadership).
Ability to diagnose technical problems, debug code, and automate routine tasks

Machine Learning Engineer
Machine Learning is a key element in Taskrabbit and we are scaling up our functional teams to provide key insights to drive our business forward.

You will be a member of the Data Group: Machine Learning, Data Science and Data Engineering. We are a force multiplier, owning the data, analysis, and knowledge infrastructure that enables ourselves and our teammates to move faster and smarter.

As a machine learning engineer, you will be working on the development and improvement of our ranking and recommendation models. You will also drive the innovative solutions for recommendation systems and will work closely with the ML infra engineers to deploy the state-of-the-art algorithms in production. You will also work with other data scientists and machine learning engineers to ensure that our models are performant, scalable and reliable to be deployed for testing.
MLE and DS - Banking Sector
Japan Digital Design (MUFG)
MUFG has vast transaction data generated from over 40 million customers. Our team apply machine learning technology to solve various challenges in the financial industry, such as fraud detection, market forecasting, credit risk and so on. We are hiring experienced and enthusiastic data scientists and machine learning engineers.
MLEs and research scientists
If you’re at KDD on Wednesday afternoon/Thursday morning, reach out to davide enyard via Whova.

Moz:// is a pioneering technology studio dedicated to building trustworthy Al. Our mission is to incubate breakthrough technologies for the open-source community. We collaborate with academic labs, industry partners and open-source collectives and translate state-of-the-art research into Al technologies that are grounded in trust, transparency and user agency. We look to challenge the dominance of closed platforms, seek to empower user choice and help foster an inclusive and healthy digital landscape. There are many potential futures possible with Al - we strive to realize the one where Al is open-source, accountable, and reliable.


• Conduct applied research on foundational models; representative areas include training, compression, multimodality, and feedback.
• Prototype and integrate emerging techniques into custom ML models.
• Design and develop rigorous frameworks for experimentation and evaluation.
• Transition research into real-world contexts by testing methods for novel use-cases.
• Guide research strategy, innovation intuition and product thinking, and help dissect problems at hand.
•Employ best practices in terms of data, development, versioning and experimentation to ensure reliability and reproducibility.
Fall/Winter 2023 Research Internship on seq. modeling
Snap Inc.
Research internship on user modeling using sequences of user actions. Reach out if interested!
Machine Learning Engineers in Meta Integrity
The teams at Meta Behavior Integrity org are looking for Machine Learning Engineers and Software Engineers to join our detection to to safeguarding people and business from harmful behavior across Facebook, Instagram and Messenger. Our mission revolves around addressing the most prevalent threats present on social media platforms, such as spam, inauthentic behavior, fraudulent ads, deceptive web pages, and phishing.

You will have the opportunity to contribute to the advancement of cutting-edge technology for combating these large-scale threats. This involves working on signal building, applying ML/AI technologies, system development, and most importantly, adapting swiftly to the ever-evolving tactics employed by adversaries.

Drop me a message or email if you are interested in.
Link: None
Senior Data Scientist
GumGum is a contextual-first, global digital advertising platform that uses advanced AI technology to serve captivating creative ads that drive consumer attention, without the use of personal data. At GumGum, we don’t need to know who you are to deliver relevant and engaging ads that align with your active frame of mind. We believe that a digital advertising industry based on context rather than personal data builds a more equitable and less invasive future for the internet and is better for consumers, publishers and advertisers alike. Our blueprint for the future, The Mindset Matrix™, combines the power of context and creative in digital advertising to deliver superior attention and drive consumer action without sacrificing personal data.

The Senior Data Scientist is responsible for developing and implementing ML solutions that enhance our ability to serve high-relevance and high-value advertisements - without tracking user behaviors. These solutions will focus on optimizing our ad-serving pathways, improving our operational decision making, and supporting a next-generation Ad Exchange Platform. The ideal candidate will have a strong foundation of statistical principles and ML techniques, experience working with petabyte-scale volumes of data, and a practiced understanding of deploying ML models to production applications.
Senior Product Manager, AI (Verity™)
GumGum is a contextual-first, global digital advertising platform that uses advanced AI technology to serve captivating creative ads that drive consumer attention, without the use of personal data. At GumGum, we don’t need to know who you are to deliver relevant and engaging ads that align with your active frame of mind. We believe that a digital advertising industry based on context rather than personal data builds a more equitable and less invasive future for the internet and is better for consumers, publishers and advertisers alike. Our blueprint for the future, The Mindset Matrix™, combines the power of context and creative in digital advertising to deliver superior attention and drive consumer action without sacrificing personal data.

We are seeking a Senior Product Manager with extensive knowledge and experience in creating AI/ML products. The Senior Product Manager will collaborate closely with our skilled team of data scientists, distinguishing between unrealistic concepts and encouraging the team to pioneer cutting-edge machine learning-based solutions.

The successful candidate is detail-oriented and a big picture thinker, helping to drive improvements to existing technology alongside innovative breakthroughs, and is challenged by solving problems across technical products at significant scale.
ML Engineer in Meta (Video Recommendation)
Meta platform
Our team works on all Facebook videos (including Reels, Long videos and Live streams) across all of our video products, which are increasingly popular across the social media industry. FB users currently spend more than a billion hours daily watching videos, making up over half of the time spent on our app globally, with projections for continued growth. Making video recommendations successful is a top priority for the company.
There are incredibly interesting ML and Ranking problems to improve video recommendations quality across all video formats to enhance user experience and engagement, driving substantial value for billions of people everyday. These are fantastic learning opportunities to work on improving a massive engagement surface through the use of advanced deep neutral net architectures, innovative ML algorithms design and industry-leading recommendation systems infra.

As ML engineer, you will drive or be part of new initiatives in improving user experience by addressing video recommendations quality gaps through state-of-the-art content and engagement modeling algorithms. You will also directly influence the definition of quality concept space, negative user actions and user sentiment modeling to improve recommendations quality.

Drop me a message or email me if you interested
Link: None
Game Data Scientist / ML (All Levels)
The Data Science team at IEG Global is dedicated to enhancing player experience and driving the growth of Tencent’s global gaming business through leading data science solutions.

The team is hiring PhD new grad, as well as experienced domain experts in multiple directions, including Marketing, Machine Learning Engineering, Generative AI, and Game Science.

1.Work on one of the following areas (depending on your expertise): Marketing, Machine Learning Engineering, Generative AI, Game Science.
2.Collaborate closely with product and engineering teams to define and execute data strategies.
3.Constantly learn the latest technologies in data science, effectively utilize advanced technologies and tools for application attempts, and explore innovation in applied research.
4.Contribute to data science best practices, processes, training, and sharing; cultivate data science culture and technical advancements.

【Position Requirements】
●M.S., or Ph.D. in a quantitative discipline such as Statistics, Math, Economics, Computer Science, Machine Learning, or equivalent practical experience.
●Excellent communication, collaboration, execution capabilities, and keen business acumen.
●Experience programming in SQL, Python, or related languages.
●Experience with generative AI applications preferred.
●Prior experience in publishing papers at top conferences in the field such as NeurIPS, ICML, AAAI, KDD, WSDM, RecSys, etc. is preferred.
●Passionate about games and the gaming industry.
Link: None
RIKEN AIP and the University of Tokyo
Conduct computer vision and AI for science research
Link: None
LLM/GPT Data Scientist
Job Summary:
We are seeking a highly skilled and experienced LLM/GPT Data Scientist to join our team. As an LLM/GPT Data Scientist, you will be responsible for designing, training, and customizing GPT architectures for LLM, image-to-text, and/or text-to-image projects. Additionally, you will apply your expertise in machine learning (ML) for computer vision (CV), generative AI architectures, and other related areas. The ideal candidate will have a strong background in Python coding, extensive experience in data science (DS), ML, and AI, and the ability to independently solve complex problems and lead project teams.

About Us:
AICADIUM is a global technology company striving to provide AI solutions across multiple industries, by leveraging a common machine learning platform to deliver industrial AI products. 
Join a growing team of data scientists, machine learning and software engineers in an agile development environment. Work together with some of the best in the field to tackle challenging projects and operationalize the solutions you develop across a variety of industries and use cases. 
We work in a casual and collaborative startup environment. Every member of the team plays a key role in shaping the solutions we develop and creating positive business value for the companies we work with. We are building a hub of the best talent in San Diego, CA and always looking for amazing talent for our headquarters in Singapore!
Machine Learning Engineer / Research Scientist (Meta Core Recommendations)
Our team works on core recommendation models and infrastructure powering results that you see across Facebook and Instagram. We design and develop novel, cutting-edge algorithms and infra solutions that are used by multi-billion users on a daily basis. Some of the areas that we work on include: large-scale recommendation models for sequences and graphs, reinforcement learning, multi-modal content understanding, responsible recommendation, online learning, distributed training, optimization algorithms, user modeling, etc. We have 20+ openings across all levels (incl new grad and leadership roles) in Bay Area, Seattle/Bellevue area, and NYC.

Please email with resume if interested.

Link: None
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