Posted 1 month ago
Simulation Lead Engineer
AI Summary
Gravis Robotics seeks a Simulation Lead Engineer to own and scale the simulation platform across Autonomy, Perception, and Platform teams, delivering high-fidelity GPU-accelerated environments, CI-integrated testing, and synthetic data pipelines.
About this role
Gravis Robotics is a startup turning heavy construction machines into intelligent and autonomous robots. Our unique combination of learning-based automation and augmented remote control enables a single operator to safely manage a fleet of earthmoving machines in a gamified environment. With over a decade of academic experience at the cutting edge of large-scale robotics, our team is rapidly translating this expertise into real-world deployments with industry leaders in a trillion-dollar market.
About the job
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
Required 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
Nice to have
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
