Google

Senior Product Manager, Gemini Post-Training, DeepMind

Google · Mountain View, California, United States · $256K–$278K/yr

Software Development · 10,001+ employees

7 h ago
Principal (10+ yrs) Full-time United States
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About the role

You will oversee the generation and integration of data across expert domains to support production-level agentic tasks. Additionally, you will define user journeys and collaborate with modeling teams to improve model generalization and evaluation.

What they look for

Product Management Artificial Intelligence Machine Learning Data Systems Agentic Frameworks Data Pipelines Dataset Curation Reinforcement Learning API Integration Context Management Stakeholder Management Cross-functional Leadership User Experience Research Product Strategy Technical Product Development

Requirements

Candidates must have a bachelor's degree in a technical field or equivalent practical experience. A minimum of 8 years in product management with a focus on AI/ML and data systems is required.

Benefits

Bonus Equity Health Insurance

Full description

Minimum qualifications:

  • Bachelor's degree in a technical field, or equivalent practical experience.
  • 8 years of experience in product management, with a focus on AI/ML, data systems, or agentic frameworks.

Preferred qualifications:

  • Proven experience in managing large-scale data pipelines, dataset curation, or environment generation for machine learning.
  • Demonstrated ability to lead cross-functional teams, shape research culture, and manage complex stakeholder relationships in highly ambiguous environments.

About the job:

At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day.

In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development.

One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users.

In this role, you will orchestrate a massive domain expansion, integrating Reinforcement Learning (RL) environments across professional verticals (e.g., science, healthcare, broader enterprise). Your work will directly address core capabilities such as long-trajectory actions (hours-long tasks), multi-step tool use on real-world APIs, and automatic context management. You will also work on translating these wins to first- and third-party harnesses to land these capabilities to millions of users.

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: $256000 - $278000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google. Responsibilities:

  • Oversee the generation and integration of data across many expert domains targeting production-level quality for hours-long agentic tasks. Define key user journeys and relevant task distributions on the basis of User Experience Research (UXR), user interviews, and engaged industry analyses.
  • Work closely with modeling teams to carefully measure and improve model generalization to real Application Programming Interface (APIs).
  • Design new internal post-training evaluations for the most critical areas, demonstrating Gemini quality across world knowledge, tool use, and context engineering.