Research Engineer, RL Engineering

Overview

As an ML Systems Engineer on Anthropic’s Reinforcement Learning Engineering team, you’ll build and improve the algorithms and infrastructure researchers use to train AI models like Claude.

What you'll do

• Build, maintain, and improve RLHF and related training algorithms and systems.
• Improve the speed, reliability, and ease-of-use of training systems.
• Profile the reinforcement learning pipeline to find optimization opportunities.
• Build systems that regularly launch training jobs in a test environment to detect pipeline problems.
• Modify finetuning systems to support new model architectures.
• Add instrumentation to detect and eliminate Python GIL contention in training code.
• Diagnose and fix training slowdowns after a number of steps.

What you'll need

• Have 4+ years of software engineering experience.
• Work on systems and tools that make other people more productive.
• Be results-oriented with a bias towards flexibility and impact.
• Pick up slack, including tasks outside your job description.
• Enjoy pair programming.
• Be interested in learning about machine learning research.
• Care about the societal impacts of your work.

Details

• Location-based hybrid policy: expected to be in an office at least 25% of the time.
• Visa sponsorship is available and supported through an immigration lawyer (not guaranteed for every role/candidate).