Robotics & Simulation Engineer, Discovery

We are seeking a Robotics & Simulation Engineer to own the simulation infrastructure, training pipelines, and deployment tooling that underpin our autonomous robotic systems. You will build and maintain the environments our RL and IL engineers train in, the telemetry systems that diagnose real-world failures, and the safety systems that protect operators and hardware during development and deployment.

Key responsibilities include:

• Owning and scaling simulation environments for RL training (Isaac Gym, Isaac Lab, MuJoCo), including terrain generation, articulated object models, and domain randomization configurations
• Building and maintaining the training-to-deployment pipeline: model export, validation, on-robot inference, and rollback
• Developing telemetry and diagnostics tooling for real-time monitoring of robot state, policy performance, and anomaly detection during field testing
• Designing and implementing safety systems: software e-stops, joint limit monitors, fall detection interlocks, and operator alert systems
• Building Isaac Sim environments for tasks requiring articulated objects (vehicle models, doors, mechanical assemblies)
• Optimizing training infrastructure for GPU cluster utilization and iteration speed
• Maintaining robot URDF/MJCF models and ensuring fidelity between sim and real

Required qualifications include:

• 3+ years of experience in robotics simulation, robot software infrastructure, or ML training infrastructure
• Experience with physics simulation tools: NVIDIA Isaac Gym/Lab, MuJoCo, PhysX, or PyBullet
• Strong software engineering skills in Python; experience with C++ a plus
• Experience with URDF/MJCF model creation and maintenance
• Working knowledge of dynamics, controls, and robotic systems
• Experience building developer tooling, dashboards, or monitoring systems
• Eligible to obtain and maintain a U.S. security clearance

Nice-to-have qualifications include:

• Experience with NVIDIA Isaac Sim / Omniverse
• Experience with distributed training infrastructure or cluster management
• Prior work deploying ML models or control policies to real-world robotic systems
• Familiarity with ROS2, robot middleware, or real-time systems
• Prior work in defense technology