As part of this role, you will

• Iterate very quickly with product teams to ship the end to end solutions for Batch and Online inference at high scale which will be used by Customers of Anyscale
• Work across the stack integrating Ray Data and LLM engine providing optimizations across the stack to provide low cost solutions for large scale ML inference. 
• Integrate with Open source software like VLLM, work closely with the community to adopt these techniques in Anyscale solutions, and also contribute improvements to open source. 
• Follow the latest state-of-the-art in the open source and the research community, implementing and extending best practices 

We’d love to hear from you if you have

• Familiarity with running ML inference at large scale with high throughput
• Familiarity with deep learning and deep learning frameworks (e.g. PyTorch)
• Solid understanding of distributed systems, ML inference challenges

Bonus points!

• ML Systems knowledge
• Experience using Ray Data
• Work closely with community on LLM engines like vLLM, TensorRT-LLM
• Contributions to deep learning frameworks (PyTorch, TensorFlow)
• Contributions to deep learning compilers (Triton, TVM, MLIR)
• Prior experience working on GPUs / CUDA 

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 ~ $247,000. 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 the following:
• Stock Options
• Healthcare plans, with premiums covered by Anyscale at 99%
• 401k Retirement Plan
• Education & Wellbeing Stipend
• Paid Parental Leave
• Flexible Time Off
• Commute reimbursement
• 100% of in-office meals covered