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Member of Technical Staff - Robotics

Job in Toronto, Ontario, C6A, Canada
Listing for: Veeda Innovation
Full Time position
Listed on 2026-08-23
Job specializations:
  • Software Development
    Robotics, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 90000 - 160000 CAD Yearly CAD 90000.00 160000.00 YEAR
Job Description & How to Apply Below

Member of Technical Staff – Robotics About Us

Veeda AI is building the next generation of multimodal foundation world models for Physical AI. We're a small, fast-moving team of engineers and researchers from leading AI labs, tackling some of the most challenging problems at the intersection of AI, robotics, and embodied intelligence. If you're excited about pushing the boundaries of what's possible with Physical AI, you'll have the opportunity to make an outsized impact from day one.

Responsibilities
  • Simulation product owner: use our simulation tooling for (post) training policies (pi-0 family, GR00T N) and provide feedback to the rest of the team.

  • Sim-to-Real Transfer: design experiments to measure the sim2real gap of our simulation stack, evaluate both simulation fidelity and policy improvements.

  • Teleoperation & Data Collection: Build and run the rigs that produce demonstration data.

  • Interface with other roboticists: learn our ML language and help us talk with customers, data providers and other collaborators who speak robot.

Requirements
  • Bachelor’s degree or equivalent hands-on experience in Robotics, Computer Science, Mechanical or Electrical Engineering, or a related technical field

  • Experience training robot policies in simulation and deploying them on real hardware

  • Strong Python and PyTorch skills; fluency in a robot software stack (ROS 2 and , or equivalent), including kinematics and camera-to-robot calibration

  • Ability to design real-world experiments with randomized initial conditions and statistically meaningful results

  • Willingness and ability to travel on-site bring up and calibrate robots

Nice to Have
  • Experience with humanoid or quadruped whole-body control, or dexterous, contact-rich manipulation with force or tactile feedback

  • Experience establishing a robot cell or data-collection operation from scratch

  • Experience post-training vision-language-action models, including RL fine-tuning of flow-based policies

  • Experience running large-scale parallel RL in Isaac Lab, Mu Jo Co  Warp, Newton, or Genesis

  • Publication or contribution to research on robot learning, imitation learning, or embodied AI

  • Contribution to open-source robot learning projects such as LeRobot, robosuite, or Mani Skill

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