Overview Research Engineer, Machine Learning (Horizons) at Anthropic. Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. Our Horizons team leads reinforcement learning research and development, with impact on Claude models such as Claude 3.5 and 3.7 Sonnet. We collaborate across alignment, red teams, applied production training, and RL engineering to build safe, scalable systems. The Horizons team sits at the intersection of cutting-edge research and engineering excellence, focusing on building high-quality, scalable systems that push the boundaries of what AI can accomplish. About the Role As a Research Engineer on the Horizons team, you will collaborate with researchers and engineers to advance the capabilities and safety of large language models. The role blends research and engineering responsibilities, requiring you to implement novel approaches and contribute to the research direction. You will work on fundamental reinforcement learning, create agentic models via tool use for open-ended tasks (e.g., computer use and autonomous software generation), enhance reasoning in areas such as mathematics, and develop prototypes for internal use, productivity, and evaluation. Representative projects Architect and optimize core reinforcement learning infrastructure, from clean training abstractions to distributed experiment management across GPU clusters; scale research workflows. Design, implement, and test novel training environments, evaluations, and methodologies for RL agents that push the state of the art for the next generation of models. Drive performance improvements across the stack through profiling, optimization, benchmarking; implement efficient caching and debug distributed systems to accelerate training and evaluation. Collaborate across research and engineering to develop automated testing frameworks, design clean APIs, and build scalable infrastructure that accelerates AI research. You may be a good fit if you Are proficient in Python and async/concurrent programming with frameworks like Trio Have experience with machine learning frameworks (PyTorch, TensorFlow, JAX) Have industry experience in machine learning research Can balance research exploration with engineering implementation Enjoy pair programming Care about code quality, testing, and performance Have strong systems design and communication skills Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems Strong candidates may have Familiarity with LLM architectures and training methodologies Experience with reinforcement learning techniques and environments Experience with virtualization and sandboxed code execution environments Experience with Kubernetes Experience with distributed systems or high-performance computing Experience with Rust and/or C++ Strong candidates need not have Formal certifications or education credentials Academic research experience or publication history Logistics Education requirements: At least a Bachelor's degree in a related field or equivalent experience. Location: Location-based hybrid policy: staff are expected to be in one of our offices at least 25% of the time, with some roles requiring more time in offices. Visa sponsorship: We sponsor visas where possible. If we make you an offer, we will make reasonable efforts to assist with visa processes. We encourage you to apply even if you do not meet every qualification. We value diverse perspectives and believe AI can benefit from inclusive teams. Compensation The expected base compensation for this position is listed below; total compensation may include equity, benefits, and incentive components. $280,000 - $425,000 USD Equal Opportunity Anthropic is an equal opportunity employer. We do not discriminate on the basis of protected status. We collect voluntary self-identification information for government reporting purposes, and participation is entirely voluntary.

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