Technical Program Manager, Discovery

Anthropic•San Francisco, CA

17h•Hybrid

About The Position

The Discovery team is organized around the north star of building an AI scientist — a system capable of solving the long-horizon reasoning challenges and core capabilities needed to push the scientific frontier. The team trains large-scale models, runs complex multi-week experiments, and builds novel products at the intersection of AI and science. As a Technical Program Manager on the Discovery team, you will own the systems and programs that determine how fast our research moves: compute planning, scientific RL environment health, and the vendor pipelines that supply them, with scope to incubate new programs in domains like bio R&D. 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 experimental 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 push the frontiers of science and benefit humanity.

Requirements

Have a background in ML engineering, ML research, or STEM R&D before transitioning to technical program management
Have deep, hands-on experience with ML training pipelines, RLHF systems, and large-scale data infrastructure in production.
Have a track record of building execution plans and inventing high-leverage processes that reduce operational overhead and let researchers focus on research.
Are a fast learner who builds deep contextual understanding in unfamiliar technical domains and can contribute meaningfully to discussions with researchers.
Are resourceful, high-agency, and able to navigate ambiguity and shifting priorities to drive progress in a fast-moving research setting
Have excellent stakeholder management and communication skills, with the ability to influence senior technical staff through clarity, competence, and consistent delivery.
Are excited about the potential for AI to accelerate scientific discovery

Responsibilities

Manage Discovery's compute planning across supervised learning (SL), reinforcement learning (RL), and sandboxing workloads, including forecasting, allocation, prioritization, and efficiency improvements. Partner with central compute planning to ensure Discovery's needs are represented and met.
Monitor the health of scientific RL environments (quality, reward integrity, failure rates) and drive issues to resolution.
Expedite the external vendor pipeline for RL environments, including quality review, reward design, and production integration.
Work with research teams across life sciences, STEM, and other scientific domains to translate research goals into roadmaps that advance AI scientist capabilities.
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.