Technical Program Manager, Gemini Post-Training, Subagents, DeepMind

Google LLC; Mountain View (CA); On-site; USD 192,000 - 278,000; Full time

Job summary

Google DeepMind in Mountain View, CA seeks a Technical Program Manager for Gemini Post-Training (Subagents). You will lead complex, multi-disciplinary engineering projects, plan requirements with internal customers, and drive programs through the full lifecycle from kickoff to delivery.

You will partner with researchers, engineers, product managers, and cross-functional stakeholders to define scope, timelines and resources, translating research priorities into training data, evaluations, and

Qualifications

• Bachelor's degree in a technical field or equivalent practical experience.
• 8 years of program management experience.
• Experience delivering with research scientists and software engineers on foundation models, agentic systems, or RL pipelines.
• Knowledge of software and ML lifecycle, compute capacity planning, and cross-functional dependencies.
• Strong stakeholder management and ability to influence without direct authority.
• Analytical depth in evaluating agentic trajectories and translating insights into interventions.

Responsibilities

• Plan requirements with internal customers and shepherd projects through the full lifecycle.
• Manage project schedules, risks, and communicate them to stakeholders.
• Collaborate with researchers, engineers, product managers, and cross-functional teams to define scope and milestones.
• Turn research priorities into high-quality training data, evaluations, and deliverable milestones.

Skills

Program management

Stakeholder management

Cross-functional collaboration

Research collaboration

RL pipelines

Education

Bachelor's degree in a technical field

Job description

corporate_fare DeepMind place Mountain View, CA, USA

Bachelor's degree in a technical field or equivalent practical experience.

• 8 years of experience in program management.

Preferred qualifications:

• 8 years of program management experience driving delivery with research scientists and software engineers on foundation models, agentic systems, or RL pipelines.
• Knowledge of software and ML development lifecycles, compute capacity planning, and experience managing complex, cross-functional dependencies.
• Strong stakeholder management skills, with the ability to navigate ambiguity, influence outcomes, and align cross-functional teams without relying on direct authority.
• Analytical depth in evaluating agentic trajectories, diagnosing failure modes, and translating insights into concrete data, harness, or RL interventions.

About the job

Google's projects, like our users, span the globe and require managers to keep the big picture in focus while being able to dive into the unique engineering challenges we face daily. As a Technical Program Manager at Google, you lead complex, multi-disciplinary engineering projects using your engineering expertise. You plan requirements with internal customers and usher projects through the entire project lifecycle. This includes managing project schedules, identifying risks and clearly communicating them to project stakeholders. You're equally at home explaining your team's analyses and recommendations to executives as you are discussing the technical trade-offs in product development with engineers.

Using your extensive technical and leadership expertise, you manage projects of various size and scope, identifying future opportunities, improving processes and driving the technical directions of your programs.

This role sits within the Gemini Post-Training team in the DeepMind GenAI unit, which researches and enables new capabilities across our Gemini models. Our team builds large language models end-to-end through SFT, RL, inference-time self-improvement and many other techniques.

As a Technical Program Manager for Gemini Post-Training (Subagents), you will apply program management methodologies across multiple post-training data, evaluation, harness, and RL initiatives, balancing rapid progress and risk to deliver improvements across Gemini. You will partner with researchers, engineers, product managers, and cross-functional stakeholders to define project scope, goals, timelines, and resource requirements, turning research priorities into high-quality training data, evaluations, and deliverable model milestones. Ultimately, you will enable subagent capabilities across Gemini Post-Training to improve both quality and efficiency across complex, long-running coding, research, and knowledge-work tasks.

Artificial intelligence will be one of humanity’s most transformative inventions. At 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: $192000 - $278000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google .

• Work with research and engineering teams to optimize subagent initiatives spanning Supervised Fine-Tuning (SFT) distillation, Reinforcement Learning (RL), and dynamic harnesses into clear goals, milestones, and release plans.
• Partner with modeling and evaluation teams to monitor evaluation leaderboards, tracking latency, token usage, parallelization speedups, and quality improvements.
• Drive convergence between research training harnesses and production agent runtimes, managing cross-functional dependencies across data, evaluations, infrastructure, and compute resources.
• Contribute to technical proposals by analyzing multi-agent trajectories, sync vs. async delegation patterns, and overall performance headroom.
• Manage end-to-end project planning using effective workflows, and translate complex modeling progress into clear, decision-ready updates for leadership and cross-functional audiences.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

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Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.