Machine Learning Systems Engineer, RL Engineering
Description For Machine Learning Systems Engineer, RL Engineering
Anthropic is seeking a Machine Learning Systems Engineer to join their Reinforcement Learning Engineering team in San Francisco. This role sits at the cutting edge of AI development, focusing on building and improving the systems that train advanced AI models like Claude.
The position requires 4+ years of software engineering experience and combines deep technical expertise with a mission-driven focus on developing safe, beneficial AI systems. You'll be responsible for critical algorithms and infrastructure that researchers use for model training, with a particular focus on RLHF (Reinforcement Learning from Human Feedback) and related methods.
Key responsibilities include profiling and optimizing reinforcement learning pipelines, building robust testing systems, adapting finetuning systems for new architectures, and implementing new training algorithms. The role requires strong software engineering skills, particularly in Python and distributed systems, along with an interest in machine learning research.
Anthropic offers a competitive compensation package ranging from $315,000 to $425,000 USD annually, along with benefits including equity donation matching, generous leave policies, and flexible working arrangements. The position requires at least 25% in-office time in San Francisco.
The company culture emphasizes collaboration, impact-focused work, and careful consideration of AI's societal implications. They view AI development as an empirical science and value diverse perspectives in their approach to building beneficial AI systems. The team works cohesively on large-scale research efforts rather than smaller, isolated projects.
This is an opportunity to work at the forefront of AI development while contributing to Anthropic's mission of creating reliable, interpretable, and steerable AI systems. The ideal candidate will combine technical excellence with a strong interest in AI safety and ethics, and a desire to work on systems that directly enable breakthroughs in AI capabilities and safety.
Responsibilities For Machine Learning Systems Engineer, RL Engineering
- Build, maintain and improve algorithms and systems for model training
- Improve speed, reliability and ease-of-use of training systems
- Profile and optimize reinforcement learning pipelines
- Build testing and monitoring systems for training jobs
- Adapt finetuning systems for new model architectures
- Diagnose and fix training performance issues
- Implement stable, fast versions of new training algorithms
Requirements For Machine Learning Systems Engineer, RL Engineering
- 4+ years of software engineering experience
- Bachelor's degree in a related field or equivalent experience
- Ability to work in office at least 25% of the time
- Experience with high performance, large scale distributed systems (preferred)
- Experience with large scale LLM training (preferred)
- Experience implementing LLM finetuning algorithms like RLHF (preferred)
Benefits For Machine Learning Systems Engineer, RL Engineering
- Competitive compensation and benefits
- Optional equity donation matching
- Generous vacation and parental leave
- Flexible working hours
- Office space for collaboration
- Visa sponsorship available
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