Research Engineer, RL Engineering

Anthropic is a public benefit corporation on a mission to create reliable, interpretable, and steerable AI systems. We are a quickly growing group of researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

As an ML Systems Engineer on our Reinforcement Learning Engineering team, you will be responsible for the critical algorithms and infrastructure that our researchers depend on to train models. You will focus on improving the performance, robustness, and usability of these systems so our research can progress as quickly as possible. Your work will directly enable breakthroughs in AI capabilities and safety.

Our finetuning researchers train our production Claude models and internal research models using RLHF and other related methods. Your job will be to build, maintain, and improve the algorithms and systems that these researchers use to train models, improving speed, reliability, and ease-of-use.

• Have 4+ years of software engineering experience
• Like working on systems and tools that make other people more productive
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming
• Want to learn more about machine learning research
• Care about the societal impacts of your work

• High performance, large scale distributed systems
• Large scale LLM training
• Python
• Implementing LLM finetuning algorithms, such as RLHF

• Profiling our reinforcement learning pipeline to find opportunities for improvement
• Building a system that regularly launches training jobs in a test environment to quickly detect problems
• Making changes to our finetuning systems so they work on new model architectures
• Building instrumentation to detect and eliminate Python GIL contention in our training code
• Diagnosing why training runs have started slowing down and fixing it
• Implementing a stable, fast version of a new training algorithm proposed by a researcher

Compensation: Annual salary $500,000—$850,000 USD.

Logistics: Minimum education: Bachelor’s degree or equivalent combination of education, training, and/or experience. Required field of study: a field relevant to the role. Years of experience required will correlate with internal job level requirements. Location-based hybrid policy: we expect all staff to be in one of our offices at least 25% of the time. Visa sponsorship: we do sponsor visas and will make every reasonable effort to get you a visa if we make an offer.

Deadline to apply: None. Applications will be reviewed on a rolling basis.