Machine Learning Systems Engineer, RL Engineering

About Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. About the Role You want to build the cutting-edge systems that train AI models like Claude. 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. Our finetuning researchers train our production Claude models using RLHF and other related methods. Your job will be to build, maintain, and improve the algorithms and systems that these researchers use. Representative Projects • Profiling the reinforcement learning pipeline to find opportunities for improvement • Building a system that regularly launches training jobs in a test environment to quickly detect problems • Making changes to finetuning systems so they work on new model architectures • Building instrumentation to detect and eliminate Python GIL contention in training code • Diagnosing why training runs have started slowing down and fixing it • Implementing a stable, fast version of a new training algorithm proposed by a researcher Compensation: $500,000 – $850,000 USD annually Anthropic offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, and flexible working hours. Hybrid policy: staff expected in office at least 25% of the time.

You May Be a Good Fit If You • Have 4+ years of software engineering experience • Like working on systems and tools that make other people more productive • Are results-oriented, with a bias towards flexibility and impact • Pick up slack, even if it goes outside your job description • Enjoy pair programming • Want to learn more about machine learning research • Care about the societal impacts of your work Strong Candidates May Also Have Experience With • High performance, large scale distributed systems • Large scale LLM training • Python • Implementing LLM finetuning algorithms, such as RLHF Minimum education: Bachelor's degree or equivalent combination of education, training, and/or experience. Minimum 4 years of software engineering experience.