Robotics Product Manager — AI/Hardware Platform

Google LLC; Greater London; On-site; GBP 144,000 - 208,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

Google DeepMind seeks a Product Manager for GDM Robotics to bridge frontier research, physical systems, and developer platforms. You will turn hard research and hardware constraints into a clear product strategy and roadmaps, partnering with researchers and engineers to bring models into real-world use with internal teams and external partners.

Depending on background, you may focus on simulation and developer experience, or physical AI safety, security, and evaluation.

Qualifications

• Bachelor's degree in Computer Science, Robotics, Mechanical/Electrical Engineering, Physics, a related technical field, or equivalent practical experience.
• 7 years of experience in product management, including taking technical products from concept to launch.
• Experience in robotics, through a robotics degree or prior work in the robotics industry.

Responsibilities

• Define product strategy, requirements, and roadmaps for GDM Robotics models and platform capabilities.
• Partner with research scientists and engineers to turn research breakthroughs into reliable products and tools.
• Establish benchmarks, evaluations, and success metrics that track model quality, safety, and real-world usefulness.
• Drive internal dogfooding and early partner deployments to pressure-test products before broad launch.
• Lead launches end to end with partners across Google, including Cloud, Responsibility & Safety, Policy, and Legal, to drive real-world impact.

Skills

Product management

Robotics

Education

Bachelor's degree in CS/Robotics/Engineering/Physics or related field

Job description

Google DeepMind seeks a Product Manager for GDM Robotics to bridge frontier research, physical systems, and developer platforms. You will turn hard research and hardware constraints into a clear product strategy and roadmaps, partnering with researchers and engineers to bring models into real-world use with internal teams and external partners.

Depending on background, you may focus on simulation and developer experience, or physical AI safety, security, and evaluation.