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Senior Product Manager, Eval Quality, AI Data

On-site in London·Added today (last checked 27 Oct)

Google

228 open roles

Our summary

Work mode
On-site, London
Experience
8+ years

Skills

Nice to have

Requirements

What we're looking for

  • Bachelor's degree or equivalent practical experience.
  • 8 years of experience in a product management, engineering, and technology strategy role.
  • 5 years of experience taking technical products from conception to launch (e.g., ideation to execution, end-to-end, 0 to 1, etc.).

Nice to have

  • Experience with LLM/GenAI evaluations, post-training/mid-training RL/SFT workflows, autoraters, or human-in-the-loop (HiTL) expert data collection.
  • Deep intuition for evaluation science—understanding what separates a brittle benchmark from a high-signal, climbable, uncontaminated evaluation across specialized verticals (e.g., finance, law, medicine, math, science, and engineering).
  • Exceptional written and verbal communication skills, with the gravitas to align Executive Team Leads, Research Scientists, and VP/SVP leadership across London and US time zones.
  • Demonstrated track record of growing across Product Area boundaries specifically balancing the changing, execution culture of research organization.

The role

Artificial Intelligence is evolving at an unprecedented pace, and AI Agents represent the next frontier. These agents, capable of complex reasoning, tool use, and interacting with dynamic environments, are poised to redefine how we live and work. Ensuring these agents are safe, reliable, and effective is paramount, and that's where evaluations come in.

Evaluations have always been the bedrock of successful AI development. However, the methods used for traditional Large Language Models fall short when it comes to agents. Unlike static models, agents operate in a world of vast possibilities, delivering value through a sequence of actions and interactions.

We need to pioneer new ways of thinking for agent evaluation. Think Waymo online: we must create rich, dynamic simulation environments to test agents against a massive state space, uncovering failure modes and ensuring robust performance across countless scenarios. This isn't just an incremental improvement; it's about defining how the next generation of AI will be validated.

If you're passionate about pushing the boundaries of AI and solving some of the most problems in the field, this is your chance. Come join our Evals team, where with products like Everest and EvalHub, we empower GenAI model development across Google. In this role, you will lead the product goal for how Google evaluates AI Agents, ensuring we build the most capable and trustworthy agentic systems in the world.

What you'll do

  • Develop a first-principles understanding of what makes an evaluation task truly useful-optimizing for coverage, climbability (scaling with compute and data while preserving headroom), discriminability, statistical stability (tight confidence intervals), and zero contamination.
  • Synthesize insights into a holistic product goal and roadmap for Eval Quality.
  • Operate seamlessly across Product Area boundaries between Gemini, AI2, and other partner product areas.
  • Grow in Gemini's dynamic, fast-moving, research-driven environment where priorities evolve rapidly and Product Managers earn trust by directly contributing to day-to-day execution.

Hiring process

4 steps3 interviewsa task to do6–8 weeks in all
  1. Apply online

  2. Assessments

    Online test · Not every role

    You may be asked to take the Google Hiring Assessment (workstyle skills) and, for some roles, role-related assessments such as a coding exercise.

  3. Recruiter conversations

    With a recruiter · Phone call · 1–2 sessions

    One or two shorter conversations assessing key skills, sharing information about the organisation and team, and asking about your preferences such as location.

  4. Project work

    In your own time · Not every role

    For some roles, a small project before interviews: a case study, writing or code samples.

  5. Interviews

    With a rotating cast of Googlers

    A panel of structured interviews, over video or in person, with a rotating cast of Googlers; open-ended role-related questions scored against the same rubric for every candidate, no brainteasers.

  6. Decision and offer · With a recruiter

  • Structured interviews: every candidate for a role is scored against the same rubric; no brainteasers.
  • AI tools are not permitted during interviews.
  • For some roles, pre-selected interviews happen virtually before final interviews onsite.

About Google

Industry
Technology
Founded
1998
Employees
100,000+
Headquarters
Mountain View, USA

In their own words

About the company & team

Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

All open roles at Google

Location

Google · London

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