Simulation Engineer

Role Overview

We are seeking a Simulation Software Engineer to take ownership of the digital twin for our partner's humanoid robot platform. This is a software-centric position where you will design and maintain simulation infrastructure critical to our controls, reinforcement learning, and hardware teams rather than simply using existing simulations.

Key Responsibilities

• Develop and extend our simulation stack built on Isaac Sim/Isaac Lab by creating custom tools, enhancements, and pipelines rather than relying solely on off-the-shelf solutions.
• Create and uphold a detailed digital twin of the humanoid robot, including accurate physics, contact dynamics, and actuator behavior, to serve as a dependable stand-in for physical hardware.
• Design software-in-the-loop (SIL) and hardware-in-the-loop (HIL) processes to rigorously validate control software prior to deployment on actual robots.
• Lead system identification efforts by tuning and calibrating simulation models to reflect real robot behavior closely, thereby minimizing discrepancies between simulation and reality.
• Construct the integral software framework linking simulation, orchestration, and data pipelines, forming foundational infrastructure rather than being a mere end-user of pre-existing tools.
• Collaborate closely with controls and robot learning teams to ensure that policies developed in simulation effectively transfer to hardware operation.

Candidate Requirements

• Solid fundamentals in software engineering with proficiency in C++ and/or Python, comfortable developing and sustaining infrastructure beyond simple scripting.
• Direct hands-on experience with robotics simulation platforms such as Isaac Sim/Isaac Lab, MuJoCo, Gazebo, or related tools.
• Background in robotics, specifically humanoid robotics, is essential as this role demands domain-specific simulation expertise rather than general game engine or VFX simulation knowledge.
• Understanding of rigid-body dynamics, contact physics, and control systems sufficient to analyze and troubleshoot why simulation models may deviate from real-world robot dynamics.
• Ability to thrive in a small, agile early-stage team environment, contributing to the establishment of core functions rather than joining mature, structured teams.

Preferred Qualifications

• Experience integrating ROS or ROS2 within simulation ecosystems.
• Previous involvement with SIL/HIL validation processes in robotics or other safety-critical systems.
• Familiarity with reinforcement learning training workflows and sim-to-real transfer methodologies.