ML Systems Engineer

Anthropic is seeking an ML Systems Engineer to join their Reinforcement Learning Engineering team, focusing on creating cutting-edge systems for training AI models like Claude. This role is perfect for someone passionate about advancing the frontier of machine learning and implementing advanced techniques for capable, reliable AI systems.

The position involves working directly with finetuning researchers who train production Claude models and internal research models using RLHF and related methods. You'll be responsible for building and maintaining the critical infrastructure that researchers depend on, with a focus on improving performance, robustness, and usability of these systems.

Anthropic operates as a public benefit corporation headquartered in San Francisco, emphasizing big science approaches to AI research. The team works cohesively on large-scale research efforts, valuing impact and collaboration over individual projects. The company's research continues important work in areas like GPT-3, Circuit-Based Interpretability, Multimodal Neurons, and AI Safety.

The ideal candidate brings 4+ years of software engineering experience and a strong desire to support research teams in building beneficial AI systems. Experience with high-performance distributed systems, LLM training, and Python is highly valued. The role offers competitive compensation ($315,000 - $425,000), comprehensive benefits, and a collaborative work environment with a hybrid setup requiring at least 25% office presence.

This position presents a unique opportunity to work at the intersection of cutting-edge AI development and safety, contributing to systems that will shape the future of artificial intelligence. The team values diversity of perspective and encourages applications from candidates who might not meet every qualification but are passionate about the societal implications of AI development.