About Anyscale: At Anyscale, we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We're commercializing Ray, a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI, Uber, Spotify, Instacart, Cruise, and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we're building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role The Anyscale Research team is looking for a strong ML Engineer and Researcher who is passionate about pushing the boundaries of what's possible with Ray. In this role, you will be instrumental in developing cutting-edge features, such as our new Accelerated DAG (ADAG) API, to establish Ray as a leader in large-scale training. You will play a key role in exploring new directions and driving our vision for Ray's future. This position is ideal for individuals with a strong engineering background and a passion for ML systems. You will spend approximately 70% of your time coding and engineering, while the remainder will focus on research to support our strategic vision and innovation. The role demands a deep understanding of ML systems and applications, including LLMs and multimodal models, with a strong emphasis on technical skills and engineering expertise. About the team We are a newly formed team dedicated to applied research in both ML modeling and systems. Our mission is to advance the capabilities of Ray and advance machine learning workloads on the Anyscale Platform. We operate at the intersection of research and engineering, collaborating closely with the Ray Core and Ray Train teams to bridge gaps and develop innovative solutions that push the frontier of ML and systems research.
\n We'd love to hear from you if haveProduction level experience in Machine Learning, and in distributed ML Systems (Python/Pytorch)4+ years experience in one of those fields: Machine Learning, NLP, or CV, or ML SystemsGraduate degree (MSc or PhD) in one of the fields abovePublished in a top-tier AI conference (Neurips, ICML, ICLR, CVPR, ACL, etc) A snapshot of projects you may work onEnhancing Ray for Large-Scale Training: Collaborate with the Ray Core and Ray Train teams to adapt and optimize Ray for efficient, large-scale GPU-heavy training, addressing current limitations and expanding its capabilities.Developing the ADAG API: Explore and potentially implement an Accelerated DAG (ADAG) API for Ray, aiming to improve performance and scalability for complex ML workflows.System Integration and Optimization: Create and refine integrations between Ray and other components, such as Ray Data, to streamline large-scale ML processes and ensure seamless operation across different systems.Research and Innovation: Contribute to cutting-edge research in ML systems, identifying new opportunities and methods to push the boundaries of what Ray can achieve in large-scale training environments.Prototype and Benchmarking: Design and build prototypes to test new features or enhancements, and conduct benchmarking to assess performance improvements and validate the effectiveness of your solutions.Work on applied research, pushing state-of-the-art on large-scale model trainingAdvance Ray as the best open source library for large-scale machine learning CompensationAt Anyscale, we take a market-based approach to compensation. We are data-driven, transparent, and consistent. The target salary for this role is $170,112 ~ $237,000. As the market data changes over time, the target salary for this role may be adjusted. This role is also eligible to participate in Anyscale's Equity and Benefits offerings, including, Stock Options
Healthcare plans, with premiums covered by Anyscale at 99%401k Retirement PlanWellness stipendEducation stipendPaid Parental LeaveFertility BenefitsFlexible Time OffCommute Reimbursement100% of in office meals covered
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