Robotics Simulation Engineer

Bachelors or Masters degree in Robotics, Computer Science, Mechatronics, Mechanical Engineering, Electrical Engineering, or a related discipline.
Open Positions: 01

Role Summary

The Robotics Simulation Engineer will design, develop, test, and virtually validate high-fidelity robotic simulation pipelines within the NVIDIA Isaac ecosystem. The role combines physics-based simulation, reinforcement learning, foundation-model integration, ROS 2 middleware, GPU containerization, and sim-to-real engineering to support reliable deployment of robotic applications in an advanced manufacturing environment.

Key Responsibilities

• Architect high-fidelity, physics-based simulation environments using NVIDIA Isaac Sim, Isaac Labs, and Omniverse.
• Create and maintain accurate USD-based robot, sensor, workstation, and factory-scene assets, including RGB-D, LiDAR, IMU, contact, and force-torque sensor models.
• Develop scalable reinforcement-learning pipelines in Isaac Gym or Isaac Labs using PyTorch, including reward design, policy architecture, parallel training, and performance optimization.
• Integrate and fine-tune embodied-AI or foundation models such as NVIDIA GR00T for manipulation, locomotion, and related robotics use cases.
• Design ROS 2 packages, nodes, lifecycle components, custom messages, action servers, and DDS communication interfaces between simulation and robot-control stacks.
• Develop modular Python automation, custom Omniverse/USD extensions, synthetic-data generation workflows, and reusable engineering tools.
• Build production-grade Docker images using CUDA, NVIDIA Container Toolkit, and compatible Omniverse runtimes for headless GPU execution.
• Implement domain randomization across visual, dynamic, friction, latency, payload, and sensor-noise parameters to improve model robustness.
• Establish software-in-the-loop and hardware-in-the-loop validation frameworks and perform system identification using real robot telemetry.
• Support deployment across local GPU workstations and approved cloud environments, with automated simulation and regression testing in CI/CD pipelines. <

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