We'd love to hear from you if have
- Production 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 Systems
- Graduate degree (MSc or PhD) in one of the fields above
- Published in a top-tier AI conference (Neurips, ICML, ICLR, CVPR, ACL, etc)
A snapshot of projects you may work on
- Enhancing 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 training
- Advance Ray as the best open source library for large-scale machine learning
Compensation
- At 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.
- Healthcare plans, with premiums covered by Anyscale at 99%
- 401k Retirement Plan
- Wellness stipend
- Education stipend
- Paid Parental Leave
- Flexible Time Off
- Commute Reimbursement
- 100% of in office meals covered
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