Simulation

Posted 10 Hours Ago
Be an Early Applicant
2 Locations
Hybrid
Senior level
Artificial Intelligence • Machine Learning • Robotics
The Role
Build a high-throughput GPU-based simulation pipeline for robotics foundation model training, implement actuators/sensors/controllers, bridge sim-to-real with policy training, and develop real-to-sim asset pipelines in collaboration with robotics and asset teams.
Summary Generated by Built In

What You’ll Do

  • Develop a high-throughput, GPU-based simulation pipeline (primarily rigid body simulation for robots) to train robotics foundation models

  • Implement essential robotics features, including actuators, sensors, and controllers, in collaboration with the robotics team

  • Work with the policy training team to bridge the sim-to-real gap

  • Develop a real-to-sim pipeline in collaboration with the asset generation team

  • Collaborate with a team of driven individuals committed to building general-purpose Physical AI

What You’ll Bring

  • Passion for your craft and demonstrated excellence in physics simulation engineering

  • Exceptional ownership and initiative—finding and solving problems independently

  • Extensive experience in physics simulation, with a preference for expertise in rigid body simulation, FEM, CFD

  • Insights and requests from a robotic researcher/engineer’s perspective for improving user experience

  • Proficiency in CUDA and GPU programming

  • Bonus: Experience in robotics control

Skills Required

  • Extensive physics simulation engineering experience
  • Proficiency in CUDA and GPU programming
  • Rigid body simulation experience
  • Experience with FEM
  • Experience with CFD
  • Robotics control experience
  • Ability to collaborate with robotics, policy training, and asset teams
Am I A Good Fit?
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The Company
86 Employees
Year Founded: 2025

What We Do

Genesis AI is a global full-stack robotics company developing general-purpose robots with human-level intelligence and capabilities. It aims to build foundational AI models that automate repetitive tasks across applications such as lab work and housekeeping. The company uses a proprietary physics engine to generate synthetic physical-world data, helping train robotics models for diverse real-world environments, and operates across Paris and Silicon Valley.

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