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# Technical Program Manager, RL Scaling, DeepMind

- **Company:** Google LLC
- **Location:** Mountain View, CA, United States
- **Experience:** Expert
- **Salary:** $217,000.0 - $236,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Bioinformatics, Reinforcement Learning, Functional Dependencies, Information Technology, Data Pipelines
- **Published:** September 9, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3387058164&tx=JT9991TTV&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Bachelor's degree in Computer Science, a related technical field or equivalent practical experience.
 * 5 years of experience in technical program management., * Master's degree or PhD in Computer Science or a closely related technical field.
 * Over 5 years leading cross-functional AI model programs, with expertise in large-scale distributed training pipelines and reinforcement learning.
 * Proven ability to design lightweight, high-impact processes that structure fast-moving research environments without hindering team velocity.
 * Highly comfortable with ambiguity; a strong communicator who builds trust and drives alignment across engineering, research, and leadership stakeholders.

## Description

* Scope, plan, and lead execution for RL research workstreams in collaboration with tech leads, turning research hypotheses into structured roadmaps, experiment plans, and deliverable model milestones.
 * Partner with engineering and infrastructure leads to manage and track experiments and compute allocations, enabling prioritization, monitoring training efficiency, and unblocking runs.
 * Identify and resolve cross-functional dependencies across the RL research ecosystem (data pipelines, evaluations, distributed infrastructure) and partner teams.
 * Establish reliable operational rhythms including experiment status dashboards, launch criteria, retrospectives, and milestone reviews, synthesizing complex training dynamics into actionable updates for tech leads and leadership.

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