Technical Program Manager, RL Research
Leads programs and execution systems for reinforcement learning research, coordinating experiments, reviews, infrastructure, and data operations. The role requires prior ML engineering or research experience, hands-on production ML infrastructure depth, and strong cross-functional program leadership.
About the job
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 organization leads to prioritize, rank, and track experiments.
- Drive research reviews end to end: set the agenda, ensure the right context is available in advance, and close the loop on decisions.
- 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.
Requirements
- 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.
- Track record of building execution plans and creating high-leverage processes that reduce operational overhead.
- Ability to quickly build contextual understanding in unfamiliar technical domains and contribute meaningfully to discussions with researchers.
- Resourcefulness, high agency, and ability to navigate ambiguity and shifting priorities in a fast-moving research setting.
- Excellent stakeholder management and communication skills, including the ability to influence senior technical staff.
- Excitement about advancing reinforcement learning at scale.
Compensation and Benefits
- Annual salary: $365,000–$435,000 USD.
- Hybrid policy: staff are expected to work from an office at least 25% of the time, with some roles requiring more office time.
- Minimum education: bachelor's degree or equivalent combination of education, training, and experience.
- Visa sponsorship is available for some roles and candidates.
- Benefits include competitive compensation, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office collaboration space.
Skills
Reinforcement Learning, Machine Learning, Ml Training Pipelines, RLHF, Data Infrastructure, Python, Experiment Tracking, Research Operations, Stakeholder Management
Similar jobs
Technical Program Management jobs
Anthropic
San Francisco, CALeads cross-functional Revenue Operations programs that improve seller productivity through GTM process, data, and systems transformations. The role requires Salesforce familiarity, strong program management and communication skills, and the ability to align stakeholders across Sales, Finance, Marketing, Legal, and Systems.
OpenAI
San Francisco, CA
Leads end-to-end software programs for AI accelerator systems, coordinating internal teams, strategic partners, and vendors from design through data center deployment. The role requires experience managing data center system products and complex software programs at scale.
OpenAI
San Francisco, CA
Leads cross-functional programs that translate model and product needs into scalable, reliable data platform, database, and storage infrastructure. The role requires deep cloud storage and data-stack expertise, architectural judgment, and experience driving complex production programs through adoption.
OpenAI
San Francisco, CA
Leads cross-functional programs that improve developer velocity and deployment excellence across ChatGPT, including CI, testing, release infrastructure, progressive rollouts, and operational validation. Requires strong technical program leadership, systems thinking, and data-driven execution across engineering teams.
OpenAI
San Francisco, CA
Leads cross-functional programs for Chat capacity planning and model deployment, connecting demand forecasting, serving capacity, launch readiness, rollout coordination, and post-deployment learning. Requires technical program leadership in infrastructure, distributed systems, model serving, or large-scale deployment environments.