About The Role

What if the physics simulations you build could teach the next generation of robots how to walk, grasp, and navigate the real world? We're looking for Robotics Simulation Engineers in the Toronto area to design, build, and optimize high-fidelity physical simulations that bridge the gap between virtual environments and real-world robotic systems.

Toronto's strength in AI research and robotics — anchored by world-class universities and a thriving tech sector — makes it a prime location for this work. You'll work at the intersection of robotics, physics, and software engineering, creating simulation pipelines that power robot learning, controls development, and hardware validation.

This is a fully remote, flexible contract role. No corporate red tape — just meaningful, technical work on problems that matter.

Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week

What You'll Do

Design and implement high-fidelity robot models (URDF/MJCF) with accurate kinematics, dynamics, and contact properties Build and maintain simulation environments using MuJoCo, NVIDIA Isaac Sim, and/or Gazebo Develop end-to-end simulation pipelines for robot training, testing, and validation Tune physics parameters — friction, damping, inertia, actuator models — to maximize sim-to-real transfer Integrate simulations with ROS2 for perception, planning, and control workflows Write clean, performant code in Python and/or C++ to support simulation infrastructure Collaborate asynchronously with robotics researchers and engineers on model accuracy and environment design Profile and optimize simulation performance for large-scale or parallelized runs Document simulation configurations, model parameters, and pipeline architecture

Who You Are

Strong hands-on experience with at least one major robotics simulator: MuJoCo, NVIDIA Isaac Sim, or Gazebo Proficient in Python and/or C++ in a robotics or scientific computing context Solid understanding of rigid-body dynamics, contact mechanics, and control theory Experience creating and validating robot models (URDF, MJCF, or SDF formats) Familiarity with ROS2 and its integration with simulation environments Comfortable working with simulation pipelines — from environment setup to data collection and evaluation Self-directed, detail-oriented, and effective when working independently Strong problem-solving instincts and a drive to close the sim-to-real gap

Nice to Have

Experience with domain randomization, sim-to-real transfer techniques, or reinforcement learning in simulation Familiarity with GPU-accelerated simulation (e.g., Isaac Gym, MuJoCo MJX) Background in legged locomotion, manipulation, or multi-body systems Experience with CI/CD for simulation testing and automated validation Knowledge of sensor simulation — cameras, LiDAR, IMUs, force/torque sensors Contributions to open-source robotics or simulation projects Graduate-level coursework or research in robotics, controls, or computational physics

Why Join Us

Work on cutting-edge robotics simulation projects that directly impact how robots learn and perform Fully remote and flexible — work when and where you're most productive Freelance autonomy with technically challenging, meaningful work Collaborate with a global community of robotics and AI professionals Gain exposure to state-of-the-art simulation frameworks and research-grade problems Potential for ongoing work and contract extension as new projects launch