Simulation Engineer

What you'll do

• Build and maintain Python pipelines and tools for closed-loop testing and synthetic data generation.
• Integrate neural rendering techniques into sensor simulation and maintain scenario libraries and benchmarks.
• Develop workflows for scenario and agent behavior generation, and work with ML and autonomy engineers to reduce sim-to-real gaps.

What they ask for

• BS, MS, or PhD in Computer Science, Electrical Engineering, Robotics, or a related field—or equivalent industry experience.
• Strong proficiency in Python.
• Experience with simulation systems, ideally in robotics, autonomous vehicles, or other high-fidelity domains.
• Eligible to work in the United States.

Nice to have

• Experience with neural rendering or generative simulation, such as Gaussian splatting, NeRFs, world models, or diffusion-based methods.
• Experience in simulation areas such as closed-loop testing, scenario design, log replay, or sensor simulation; benchmark development; synthetic data pipelines; or real-time robotics.

Tools

Python, Gaussian splatting, NeRFs, world models, diffusion-based methods

AI focus

The role applies neural rendering and generative simulation to sensor simulation and synthetic data generation. AI tools may also be used during interviews to compare applicants’ qualifications with the job description; a human reviews the output and makes the final decision.