Lead Prototyping Engineer/machinist, Deepmind

Google Google · Big Tech · Cambridge, MA +1

This role is for a Lead Prototyping Engineer/Machinist on Google DeepMind's Robotics team, focused on building physical systems for Embodied AI. The role involves leading the end-to-end manufacturing of core hardware, bridging the gap between AI research and physical reality, and working closely with researchers to deliver hardware prototypes.

What you'd actually do

  1. Program, set up, and operate high-end multi-axis fleets to produce complex cylindrical, prismatic, and organic geometries.
  2. Maintain sub-thousandth precision through routine 5-axis kinematic calibration, tramming, and rigorous first-article inspections using Coordinate Measuring Machines (CMMs) and optical comparators.
  3. Design and manufacture custom CAD workholding solutions and establish standardized, optimized CAM tool libraries.
  4. Apply first-principles machining to Titanium, PH stainless steels, and Inconel 718, including in-house heat treatment for rapid prototype cadences.
  5. Drive shop floor excellence, manage specialized gear manufacturing cycles, and optimize project workflows using Fulcrum Pro.

Skills

Required

  • Computer Numerical Control (CNC) machinist in an R&D environment
  • modern CAD platforms (Onshape and SolidWorks)
  • Geometric Dimensioning and Tolerancing (GD&T) standards (ASME Y14.5 and ISO GPS)

Nice to have

  • CNC prototype gear manufacturing using Mill-Turn machines (e.g., hobbing, skiving, or custom gear cycles)
  • machining and tooling strategies required for 17-4 PH, 15-5 PH, and Inconel 718
  • simultaneous 5-axis milling and complex multi-axis mill-turn programming and operation
  • high-end control architectures, specifically Heidenhain, Siemens (840D/Sinumerik One), or Okuma OSP
  • significant contributions in high-velocity, technology-first industries such as Formula 1, elite motorsports, Robotics Research and Development labs, or Automotive Skunk Works

What the JD emphasized

  • zero-to-one manufacturing
  • high-impact role
  • low-volume, high-complexity environments
  • time is the primary commodity of scarcity
  • manufacturing engineer capable of looking at a "no-bid" or conceptually incomplete design, filling in the blanks, and determining the optimal strategy to bring it to life
  • exacting tolerances
  • constructive Design for Manufacturability (DFM) guidance
  • own the prototyping process end-to-end
  • working in daily lockstep with researchers
  • deliver hardware out of novel materials for extreme environments
  • high-velocity, technology-first industries

Other signals

  • Embodied AI
  • Robotics team
  • Hardware for AI models
  • Zero-to-one manufacturing
  • Prototyping