Machine Learning Systems Engineer, RL Engineering

Anthropic • San Francisco, CA

69d • $300,000 - $405,000

About The Position

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

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.
• Ability to pick up slack outside of job description.
• Enjoy pair programming.
• Desire to learn more about machine learning research.
• Awareness of the societal impacts of work.

Nice To Haves

• 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.

Responsibilities

• Build, maintain, and improve the algorithms and systems used by finetuning researchers to train models.
• Improve the speed, reliability, and ease-of-use of training systems.
• Profile the reinforcement learning pipeline to find opportunities for improvement.
• Build a system that regularly launches training jobs in a test environment to quickly detect problems in the training pipeline.
• Make changes to finetuning systems to work on new model architectures.
• Build instrumentation to detect and eliminate Python GIL contention in training code.
• Diagnose and fix issues causing training runs to slow down after a number of steps.
• Implement stable, fast versions of new training algorithms proposed by researchers.

Benefits

• Competitive compensation and benefits.
• Optional equity donation matching.
• Generous vacation and parental leave.
• Flexible working hours.
• Lovely office space for collaboration.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Publishing Industries
• Education Level: Bachelor's degree