Research Engineer, RL Engineering
San Francisco, CA | New York City, NY | Seattle, WA
Posted 23h ago
Job Location
San Francisco, CA | New York City, NY | Seattle, WA
Tech Stack
Remote Work Policy
On-site
Categories
AI Research Engineer
About the job
Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. As an ML Systems Engineer on the Reinforcement Learning Engineering team, you will build and improve the critical algorithms and infrastructure that researchers use to train AI models like Claude. Your work will directly enable breakthroughs in AI capabilities and safety, focusing on enhancing the performance, robustness, and usability of these systems to accelerate research progress. You will support and empower the research team in their mission to build beneficial AI systems, specifically by building, maintaining, and improving the algorithms and systems used for finetuning production and research models with methods like RLHF.
Responsibilities
- Build, maintain, and improve algorithms and systems for training AI models.
- Enhance the speed, reliability, and ease-of-use of AI training systems.
- Support researchers by providing robust and efficient tools for model training.
- Profile and optimize reinforcement learning pipelines for performance improvements.
- Develop systems for automated testing of training pipelines.
- Adapt finetuning systems to work with new model architectures.
- Implement instrumentation to detect and resolve performance bottlenecks like Python GIL contention.
- Diagnose and fix performance degradation in training runs.
- Implement new training algorithms proposed by researchers.
Requirements
- 4+ years of software engineering experience.
- Experience working on systems and tools that enhance productivity.
- Results-oriented with a bias towards flexibility and impact.
- Willingness to take initiative and contribute beyond the immediate job description.
- Enjoyment of pair programming.
- Desire to learn more about machine learning research.
- Care about the societal impacts of AI work.
- Experience with high-performance, large-scale distributed systems.
- Experience with large-scale LLM training.
- Proficiency in Python.
- Experience implementing LLM finetuning algorithms, such as RLHF.
Benefits
- Annual compensation range: $500,000 - $850,000 USD
- Visa sponsorship available for some roles and candidates.
- Encouragement to apply even if not all qualifications are met.
- Commitment to diversity and inclusion.