Simulation Lead Engineer

Description

At Gravis, we operate at the intersection of hardware, software, and real-world deployment. Our Rooftop Autonomous Control Kit (RACK) integrates sensing, compute, communication, and networking into a manufacturer-agnostic solution deployable across a wide range of construction machines. As the Gravis Simulation Lead Engineer, you will own the entire simulation landscape at Gravis. You'll define the architecture, implement it, set the strategy, and build the infrastructure that powers simulation-based software testing, automated regression testing, ML policy training, and synthetic data generation across our Autonomy, Perception, and Platform teams. This is a high-impact role at the intersection of all our deep technical disciplines. We expect this role to quickly grow into a technical team lead position.

Responsibilities

• Own and drive the roadmap for Gravis's simulation platform: architecture, implementation, tooling, infrastructure, and long-term strategy
• Build and maintain high-fidelity simulation environments in GPU-accelerated simulation tailored to heavy construction machinery: terrain, sensors, hydraulics, soil dynamics, …
• Design and implement automated simulation testing, regression pipelines, and CI integration
• Develop synthetic data generation and domain randomization pipelines to support ML policy training and perception model development
• Actively close the sim-to-real gap: instrument & analyse simulation/real-world mismatches
• Collaborate with Autonomy, Perception, and Platform teams to gather and translate requirements into simulation capabilities to enable them in their mission
• Build and manage the compute infrastructure to run simulation workloads continuously at scale (in-house and cloud-based)
• Recruit and technically lead simulation engineers

Qualifications

• Bachelor's or Master's in Computer Science, Robotics, or a closely related field
• 5+ years of experience in robotics simulation or a related field, or results that make years of experience irrelevant
• Hands-on experience with GPU-accelerated simulation software
• Strong software engineering skills in Python. We expect production-quality code
• Experience integrating simulation into CI pipelines and automated testing frameworks
• Excellent communication skills in English
• Experience hiring or technically leading engineers, or willingness to do so
• Experience with GPU-based simulation and large-scale cloud simulation infrastructure (AWS, containerization, provisioning tools)
• Familiarity with CI/CD systems (GitHub Actions, Jenkins, or similar)
• Knowledge of reinforcement learning or imitation learning for robot policy training
• Knowledge of closing sim-to-real gap
• Strong software engineering skills in modern C++
• Experience with ROS2