Lead GPU Simulation Engineer Robotics Autonomy

Lead Simulation Engineer - Startup / GPU / Python

Our client is a well-funded, venture-backed robotics startup based in Zurich, operating at the frontier of autonomous heavy machinery. Their technology combines learning-based automation and remote operation to enable a single operator to manage an entire fleet of construction machines in the field.

They are looking for a Lead Simulation Engineer to own the entire simulation platform end-to-end: architecture, tooling, infrastructure, and long-term strategy.

You will build GPU‑accelerated, high‑fidelity environments tailored to heavy construction machinery, covering terrain, sensors, hydraulics, and soil dynamics, and develop pipelines for ML policy training, synthetic data generation, and automated regression testing.

You will work closely with their Autonomy, Perception, and Platform teams, and the role is expected to grow into a technical team lead position quickly.

If you want to work on the sim‑to‑real gap for some of the most complex machines on the planet, this is the role.

• Define the simulation roadmap and own architecture, implementation, and infrastructure
• Build high‑fidelity GPU‑accelerated environments for heavy construction machinery
• Design automated testing, regression pipelines, and CI integration
• Develop synthetic data generation and domain randomisation pipelines for ML
• Instrument and analyse simulation/real‑world mismatches to close the sim‑to‑real gap
• Build and manage compute infrastructure for continuous simulation workloads at scale
• Recruit and technically lead simulation engineers as the team grows

• Bachelor’s or Master’s in Computer Science, Robotics, or a related field
• 5+ years in robotics simulation, or results that make years of experience irrelevant
• Hands‑on experience with GPU‑accelerated simulation software
• Experience integrating simulation into CI pipelines and automated testing frameworks
• Experience hiring or technically leading engineers, or a clear willingness to do so

• CI/CD systems such as Git Hub Actions or Jenkins
• Reinforcement learning or imitation learning for robot policy training
• Strong C++ skills and experience with ROS2

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