Minimum qualifications:- Bachelor's degree or equivalent practical experience.
- 8 years of experience in technical program management.
Preferred qualifications:- 4 years of experience working in the field of robotics and computer vision.
- Excellent project manager and takes initiative, with the ability to work separately and on multiple initiatives at the same time.
- Excellent problem-solving skills, strategic and investigative capabilities.
About the jobGoogle'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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $256000 - $279000 (USD) 20% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Lead the planning and execution of complex, multi-disciplinary technical programs for Gemini Robotics, from foundational research to real-world deployment.
- Partner closely with executive research and engineering leaders to translate high-level strategy into actionable program roadmaps, setting clear goals and objectives.
- Drive programs that integrate large-scale AI models (Gemini) with physical robotics platforms, addressing unique challenges in latency, safety, and real-world generalization.
- Oversee or contribute significantly to the data strategy for robotics, ensuring high-quality data collection, processing, and compliance to support model training.
- Identify and manage complex risks, dependencies, and changing circumstances in a fast-paced research environment.
