Technical Program Manager, Gemini Evals, DeepMind

Minimum qualifications: Bachelor's degree in Computer Science, Engineering, Data Science, related technical field, or equivalent practical experience. 5 years of experience leading engineering projects across multiple geographies and time zones. Preferred qualifications: Experience in people management. Experience in Large Language Model (LLM) evals, 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. 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. 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 - $237000 (USD) + 15% bonus target + equity + 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. Drive strategic goals and tactical delivery. Lead with high agency. Proactively identify workflow gaps and implement scalable improvements to optimize efficiency and output quality. 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. #J-18808-Ljbffr Socket.dev