Senior Technical Program Manager Lead, Gemini Audio, Deepmind

Google Google · Big Tech · Mountain View, CA +2

Senior Technical Program Manager Lead for Gemini Audio at Google DeepMind, focusing on end-to-end model quality across the AI lifecycle. The role involves collaborating with researchers, data scientists, and serving/deployment teams to manage model training priorities, design and execute evaluations, and oversee the entire release cycle for foundational audio models. This includes checkpoint uploads, documentation, deployment coordination, capacity planning, and cross-functional testing, with a strong emphasis on applying deep AI evaluation methodologies and driving strategic outlook with high agency.

What you'd actually do

  1. Collaborate with modeling and capability teams to track training priorities, analyze evaluation and experimentation results, and coordinate feedback to improve models.
  2. Apply deep AI evaluation methodologies, working with data scientists to design and execute evals and perform loss analysis to measure and improve model quality.
  3. Manage the entire release cycle, including checkpoint uploads, documentation, deployment/serving coordination, capacity planning, and cross-functional testing.
  4. Provide proactive status updates to stakeholders and triage model issues back to development teams.
  5. Drive strategic outlook with high agency, proactively fixing workflow gaps to scale efficiency and output quality.

Skills

Required

  • 10 years of experience in program management
  • 7 years of experience in leadership role(s) with/without direct reports
  • Bachelor's degree in a technical field, or equivalent practical experience

Nice to have

  • Experience working on foundational models, in the audio space
  • Experience in model training, model releases, or data science
  • Ability to quickly learn and understand the technical aspects of the programs from interface to infrastructure, serving, and customer issues, and drive technical discussions
  • Ability to manage complex stakeholder relationships

What the JD emphasized

  • end-to-end model quality
  • foundational models
  • audio space
  • model training
  • model releases
  • serving/deployment
  • evaluation methodologies
  • release cycle

Other signals

  • end-to-end model quality
  • foundational models
  • audio space
  • model training
  • model releases
  • serving/deployment
  • evaluation methodologies
  • release cycle