Technical Program Manager, RL Research

Anthropic•San Francisco, NY

2d•Hybrid

About The Position

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. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Our Reinforcement Learning teams are central to advancing our AI systems, contributing to every Claude model and driving the autonomy and coding gains in our latest releases. The work spans computer use, code generation through RL, fundamental RL research for large language models, scalable infrastructure and training methodologies, and model reasoning. The Research TPM team supports the full model development lifecycle, from pre-training through post-training, operating at the frontier of AI development. As a Technical Program Manager on the reinforcement learning team, you will own the systems and programs that determine how fast our research moves: a trustworthy read on the state of RL research, the review and prioritization processes that turn that read into critical decision for production RL runs. Strong candidates should have an ML engineering or research background and have grown into program leadership. You'll need real technical depth: the ability to debug data pipelines, read RL transcripts to spot issues, and make allocation and quality decisions in real time when research or production runs hit problems. You'll need organizational effectiveness in equal measure: the ability to navigate a fast-growing organization, quickly identify the critical people and teams across research, infrastructure, product, and data operations, and coordinate across them without losing velocity. Join us in our mission to build AI systems that are safe, reliable, and beneficial to humanity.

Requirements

A background in ML engineering or ML research before transitioning to technical program management
Deep, hands-on experience with ML training pipelines, RLHF systems, and large-scale data infrastructure in production
A track record of building execution plans and inventing high-leverage processes that reduce operational overhead and let researchers focus on research
Fast learner who builds deep contextual understanding in unfamiliar technical domains and can contribute meaningfully to discussions with researchers
Resourceful, high-agency, and able to navigate ambiguity and shifting priorities to drive progress in a fast-moving research setting
Excellent stakeholder management and communication skills, with the ability to influence senior technical staff through clarity, competence, and consistent delivery
Excited about pushing the frontier of what RL can do at scale

Responsibilities

Deliver a regular read on the ground truth in RL research, covering performance against baselines, experiment results, day-to-day health, and incidents
Work with RL org leads on prioritizing, ranking, and tracking the state of experiments
Drive research reviews end to end in partnership with set the agenda, make sure the right context is in the room ahead of time, and close the loop on what gets decided
Establish processes and frameworks that bring structure to an unstructured research setting without slowing researchers down
Collaborate with research leads, infrastructure engineers, and data operations to identify blockers, prioritize competing needs, and make technical trade-off decisions