Software Technical Lead, On-device Inference Software, Robotics, Deepmind

Google Google · Big Tech · Mountain View, CA +1

Technical Lead for On-Device Inference Software in Robotics at Google DeepMind, focusing on running advanced AI models (Gemini Robotics, VLA) on embedded hardware for robots. Responsibilities include software strategy, execution, cross-functional team coordination, system optimization for inference, and ensuring model security and performance on edge devices. Requires strong software engineering foundation, experience with system-level software, and embedded compute platforms.

What you'd actually do

  1. Lead the software architecture and development for on-device inference, ensuring system readiness for external deployments.
  2. Coordinate and drive engineering efforts across multiple cross-functional teams to deliver critical system components.
  3. Ensure consistency, performance, and robust model security across the entire hardware and software integration layer.
  4. Optimize system software to run state-of-the-art Vision Language Action (VLA) models like Gemini Robotics efficiently and seamlessly on edge devices.

Skills

Required

  • Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience.
  • 8 years of experience leading and delivering full-stack system software projects.
  • 3 years of experience with system-level software components such as operating systems, firmware, and compilers.
  • Experience in software development with advanced embedded compute platform such as the Nvidia Jetson Thor, or Qualcomm IQ-X.

Nice to have

  • Master’s degree or PhD in Computer Science, Electrical Engineering, Robotics, or a related field.
  • Experience with on-device AI inference for robotics, automotive, or related use cases.
  • Demonstrated engineering leadership experience, with a strong track record of driving large-scale, cross-organizational technical initiatives.
  • Demonstrable expertise with JAX or PyTorch and related foundational technologies (XLA, CUDA).
  • Familiarity with foundation models and the unique computational and security demands of running them in physical, interactive robotics environments.
  • Strong communication skills with the ability to articulate complex safety requirements to various research, hardware, and software engineering teams.

What the JD emphasized

  • on-device inference
  • Gemini Robotics models
  • embedded hardware
  • system software stack
  • state-of-the-art Vision Language Action (VLA) models
  • edge devices

Other signals

  • on-device inference
  • robotics
  • Gemini Robotics models
  • embedded hardware
  • system software stack
  • Technical Lead