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Jobs Posted on the Whova Community Board of MLOps World + Generative AI World Summit 2023

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Contract | Dbt plugin developer
Develop a dbt plugin
Senior MLOPs Engineer
MD Anderson
We are actively recruiting a Senior Data Scientist serving as a technical lead to drive the development, operationalization, and usage of an ML Ops pipeline to support the clinical translation of computer vision algorithms.

The MLOps stack will combines cloud services and other software to train, deploy and manage production quality computer vision algorithms. The focus is to enable rapid experimentation, deployment, and integration of computer vision models to enable researchers to robustly evaluate the impact of their solutions. The candidate will help shape infrastructure-as-code to develop, deliver, and maintain the MLOps pipeline, working closely with cloud-ops teams, integration teams, and other vital stakeholders to ensure effective implementation and integration with health IT systems. The candidate work with research data scientist, ML engineers, clinicians, and other stakeholders to ensure the solution maximizes observability across the AI development lifecycle, and integrate with analytics to ensure solutions are performant, impactful, and secure.
Machine Learning Engineer
MD Anderson Cancer Center
We are in search of an ML engineering to play a pivotal role in propelling the development, validation, and deployment of high-quality computer vision AI algorithms to automate treatment planning and treatment monitoring in radiation oncology. In this role, the individual will oversee the lifecycle of AI models, encompassing training, evaluation, and deployment, of image analysis algorithms. This position will see the individual working within a collaborative team of researchers, data scientists, and ML engineers to develop and operationalize machine learning models. As a crucial team member, the individual is responsible for the rigorous testing, versioning, and documentation, ensuring impact, risk mitigation, and reproducibility. Additional responsibilities include user-acceptance testing, user training, algorithm monitoring, and effective stakeholder engagement.
The individual will also contribute to our educational sphere. They will be instrumental in developing a culture of rapid experimentation through high quality development and automation, while minimizing bias, enhancing fairness, and maximizing transparency in AI models. They will educate and train research data scientists on ML engineering best practices and responsible AI practices. They will engage with stakeholders to gather requirements, convey AI concepts understandably, incorporate feedback, and ensure sustainable impact.
Generative AI Engineer
Are you passionate about pushing the boundaries of AI to deliver innovative solutions? At PLACE, we are at the forefront of transforming the real estate lifecycle using AI-driven technologies.

What You’ll Do:
Architect and Innovate: Develop high-end natural language understanding applications using Python and JavaScript, ensuring flawless integration with our legacy systems.
Be at the AI Forefront: Lead the development of applications for AI giants like GPT-3/GPT-4. Transition these from proof-of-concept stages to production, ensuring robustness and reliability.
ML Mastery: Design, develop, and optimize machine learning models for applications ranging from text classification to recommendation systems.
Collaborative Leadership: Offer technical guidance in Agile Sprints, working closely with cross-functional teams. Your insights will be pivotal in driving innovation and ensuring timely project completion.
Code Excellence: Champion high-quality coding practices, conducting in-depth code reviews to spot bugs, improve performance, and nurture best practices.

What We’re Looking For:
Tech Pro: Proven expertise in Python and JavaScript, having worked on intricate AI projects.
AI Guru: Deep experience in natural language applications, especially around Information Retrieval and Generative AI Systems.
Framework Fanatic: Hands-on skills with frameworks like TensorFlow, PyTorch, and XGBoost,Langchain
Cloud Champion: Proficient in AWS services, especially Lambda, EFS, Vector Databases, and DynamoDB.
AI Enthusiast: Acquaintance with advanced ML models such as GPT-3/4, T5, and BERT.
Integration Expert: A proven track record of integrating third-party APIs into AI systems.
Team Player: Stellar communication skills, adept at collaborating with various teams and breaking down tech jargon.
Agile Ace: Proven leadership in Agile environments, steering teams towards success.
Frontend Software Engineer
We are seeking a highly skilled software engineer to design and develop platforms that support and facilitate AI model development for the Perception component of our autonomous driving stack. In this role, you will work closely with Machine Learning engineers, data scientists, and software engineers to build scalable and high-performance applications that enable ML engineers to efficiently curate and build model training datasets, as well as evaluate their models across PBs of multimodal data. You will be responsible for conducting the design and implementation of the frontend application of various MLOps systems, ensuring that they follow best practices to maximize the tooling efficiency and ML engineers’ productivity.

MLOps Engineer
Senior ML Platform Engineer - Artificial Intelligence Group

The AI Group is the central engineering group responsible for driving Machine Learning (ML) adoption at Bloomberg, with over 200 researchers and engineers working together to provide clients with the best-in-class news, research, market data, and analytics using innovative machine learning technology. We directly impact a wide variety of our flagship products, including news, research, pricing, communications platforms, search and discovery tools. We work on a variety of ML fields, including natural language processing, information retrieval, time series analysis, and recommender systems.

Within the AI Group, the AI Platform team builds systems to help accelerate the development, deployment, and maintenance of scalable AI services. Our group’s mission is to standardize, simplify, and scale the development, deployment and maintenance of all machine-learning-based solutions at Bloomberg built on top of cloud native and open source technologies.

While working on the team as an ML Platform Engineer, you will have the opportunity to create a more cohesive, integrated, and managed ML model development life cycle. Typical activities include:

Architecting, building, and diagnosing production ML systems
Working closely with ML application teams to design seamless workflows for continuous model training, inference, and monitoring
Defining and providing strong SLAs around latency, throughput and resource (memory / disk / network / CPU / GPU) usage
Interfacing with both ML experts and platform engineers to understand workflows, pinpoint and resolve inefficiencies, and inform the next set of features for the platforms
Collaborating with open-source communities and internal platform teams to build a cohesive MLOps experience
Troubleshooting and debugging user issues
Providing operational and user-facing documentation
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