Senior/Staff Machine Learning Engineer, Sensor Simulation

What the role actually is Nuro is hiring a senior or staff ML engineer to build synthetic sensor simulation for autonomous driving. The listing focuses on methods that generate realistic camera, lidar, or radar data and then measure whether that simulated data improves autonomy performance. The role sits between sensor modeling, modern ML graphics, evaluation, and production autonomy. Nuro explicitly mentions NeRF, Gaussian splatting, generative models, and real sensor noise as relevant areas. What you would work on Research and implement synthetic sensor simulation methods Characterize the realism and utility of generated sensor data Answer evaluation questions about how sensor data affects autonomy performance Collaborate with autonomy, infrastructure, and systems teams on simulation needs What they are asking for ML, robotics, computer science, or electrical engineering background Hands-on experience training and evaluating modern ML models Strong Python skills and experience with deep learning frameworks Experience with sensor modeling, 3D geometry, generative methods, or ML pipelines is a plus Why this one is worth a look Simulation quality is becoming a product constraint for autonomy teams. This role is interesting because it is not just building synthetic scenes; it is about whether simulated sensors actually help a robot learn, validate, and ship safer behavior. #J-18808-Ljbffr The Robot Age