Senior Synthetic Data Engineer - Autonomous Driving

Job description

Job responsibilities

• Build, implement, and optimize tools to generate synthetic data for training different deep learning DRIVE networks, including simulated lidar, radar, camera/RGB-D, bounding boxes, object tracks, world models,…
• Develop lidar and radar sensor simulation workflows that run against NuRec reconstructed driving worlds and Cosmos-generated environments, including sensor placement, calibration, material response, geometry handling,…
• Develop Cosmos world model for better world generation, encompassing controllable scenario generation, novel view synthesis, trajectory extrapolation, scene completion, quality triage, regression detection, and…
• Collect perception, planning, and deep learning DRIVE network requirements and match them to current synthetic data and sensor simulation features. Develop new tools and improve performance when gaps are found.
• Develop dataset quality assessments and synthetic-real comparison procedures that evaluate sensor realism, annotation quality, distribution coverage, scenario diversity, and sim-to-real transfer for autonomous driving.
• Set up, profile, and supervise large-scale NuRec, Cosmos, and sensor simulation pipelines in data center or cloud environments.
• Debug cross-stack systems spanning sensors, reconstruction models, world models, simulation runtime, GPU workloads, distributed data services, and downstream autonomous-driving workloads.