Technical Program Manager, RL Scaling, DeepMind

Google DeepMind; Mountain View (CA); On-site; USD 217,000 - 236,000; Full time

Benefits offered by this job

Bonus target

Equity

Benefits

Job summary

Google DeepMind's Gemini Reinforcement Learning Scaling team leads cutting-edge research for large language models, driving reasoning, multimodal, and agentic capabilities that define future Gemini releases.

As a Technical Program Manager, you will independently drive RL research workstreams, partner with researchers to operationalize scaling experiments, manage training pipelines (including SFT initialization and data workflows), optimize compute utilization, and accelerate breakthroughs into

Qualifications

• Bachelor's degree in Computer Science or related field or equivalent practical experience.
• 5 years of experience in technical program management.

Responsibilities

• Scope, plan, and lead RL research workstreams with tech leads, turning hypotheses into roadmaps and milestones.
• Partner with engineering and infra leads to manage experiments and compute allocations for prioritization and efficiency.
• Identify and resolve cross-functional dependencies across data pipelines, evaluations, and distributed infrastructure.
• Establish operational rhythms like dashboards, launch criteria, and reviews for leadership updates.

Skills

Technical program management

Cross-functional leadership

RL research collaboration

Communication with leadership

Education

Bachelor's degree in CS or related field

Advanced degree (MS/PhD) in CS or related field

Job description

Minimum qualifications:

• Bachelor's degree in Computer Science, a related technical field or equivalent practical experience.
• 5 years of experience in technical program management.

Preferred qualifications:

• 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.

About The Job

The Gemini Reinforcement learning (RL) Scaling team is at the frontier of reinforcement learning research for large language models, driving the reasoning, multimodal, and agentic capabilities that define the next generation of Gemini models.

As a Technical Program Manager, you will independently drive program execution for critical RL research workstreams. You will sit at the intersection of empirical research and large-scale distributed systems, partnering directly with research scientists and research engineers to operationalize scaling experiments, manage RL training pipelines including SFT initialization and data workflows optimize compute utilization, and accelerate the progress of research breakthroughs into frontier Gemini releases.

Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $217000 - $236000 (USD) + 15% bonus target + equity + benefits

Responsibilities

Learn more about benefits at Google .

• 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.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .