ML Systems Engineer

Anthropic is seeking an ML Systems Engineer to join their Reinforcement Learning Engineering team, focusing on building cutting-edge systems for training AI models like Claude. This role is perfect for engineers passionate about advancing AI capabilities while ensuring safety and reliability. You'll be working at the frontier of machine learning, implementing and improving advanced techniques for model training.

The position involves working with finetuning researchers who train production Claude models and internal research models using RLHF and related methods. Your primary responsibility will be developing and maintaining the critical algorithms and infrastructure that researchers depend on. This includes improving system performance, robustness, and usability to accelerate research progress.

Anthropic operates as a public benefit corporation, emphasizing big science approaches to AI research. The team works cohesively on large-scale research efforts, prioritizing impact and the development of steerable, trustworthy AI. The collaborative environment includes frequent research discussions and values strong communication skills.

The role offers competitive compensation ($315,000 - $425,000), comprehensive benefits, and a hybrid work arrangement in San Francisco. Anthropic actively sponsors visas and promotes diversity in their team, recognizing the importance of varied perspectives in AI development. The company's research builds on significant work in areas like GPT-3, Circuit-Based Interpretability, and AI Safety.

This position is ideal for candidates with 2+ years of software engineering experience, particularly those interested in high-performance distributed systems and LLM training. The role demands a results-oriented approach, flexibility, and a genuine interest in advancing beneficial AI development while considering its societal implications.