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Salary: USD 365,000 - 435,000 / annual
Anthropic is seeking a Technical Program Manager to support its Reinforcement Learning research teams, which are central to advancing Claude models and driving autonomy and coding capabilities. The RL teams work across computer use, code generation through RL, fundamental RL research for large language models, scalable infrastructure, training methodologies, and model reasoning.
In this role, you will own the systems and programs that determine research velocity. You'll deliver regular assessments of RL research ground truth, covering performance against baselines, experiment results, day-to-day health, and incident tracking. You'll work with RL org leads on prioritizing and tracking experiments, and drive research reviews end-to-end—setting agendas, ensuring proper context, and closing the loop on decisions.
Key responsibilities include establishing processes and frameworks that bring structure to research settings without slowing researchers down, and collaborating with research leads, infrastructure engineers, and data operations to identify blockers, prioritize competing needs, and make technical trade-off decisions.
Ideal candidates have backgrounds in ML engineering or ML research before transitioning to technical program management. You should have deep, hands-on experience with ML training pipelines, RLHF systems, and large-scale data infrastructure in production. You'll need a track record of building execution plans and inventing high-leverage processes that reduce operational overhead. Strong technical depth is essential—you must be able to debug data pipelines, read RL transcripts to spot issues, and make allocation and quality decisions in real time. Equally important is organizational effectiveness: navigating a fast-growing organization, identifying critical people and teams across research, infrastructure, product, and data operations, and coordinating across them without losing velocity. You should be a fast learner who builds deep contextual understanding in unfamiliar technical domains, resourceful with high agency, and able to navigate ambiguity and shifting priorities. Excellent stakeholder management and communication skills are required, with the ability to influence senior technical staff through clarity, competence, and consistent delivery.
