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 various Engineering-specific programs and teams.

The Gemini Evals team is responsible for developing new ways to test and measure model performance. This is an open-ended problem that requires close collaboration between research and engineering and applying the state of the art AI/ML to conversational problems.

Artificial intelligence will be one humanity’s most transformative inventions. At Google Deep Mind, 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.

The US base salary range for this full-time position is $256,000-$278,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Collaborate closely with the engineering team to support infrastructure development, meticulously track priorities, issues, deeply understand evaluation and experimentation results, coordinate alignment and, assessment with model teams.

• Collaborate with data scientists to design and integrate model evals, execute evals, and conduct loss analysis to inform model quality.

• Manage Gemini autorater platform and Gemini Eval area compute capacity planning. Provide proactive status updates to stakeholders, and effectively triage autorater issues back to the modeling team.

• Guide strategic goal and tactical delivery. Lead with high agency. Proactively identify workflow gaps and implement scalable improvements to optimize efficiency and output quality.

Minimum qualifications

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

• 8 years of experience leading engineering projects across multiple geographies and time zones.

• 3 years of experience in people management.

Preferred qualifications

• Experience in Large Language Model (LLM) evaluations, model training, model releases, or data science.

• Ability to quickly learn and deeply understand the technical aspects of the programs from interface to infrastructure, serving, and customer issues, and drive technical discussions.

• Excellent skills in managing complex stakeholder relationships.