Note: The job is a remote job and is open to candidates in USA. NVIDIA develops software-defined platforms for autonomous vehicles, including simulation technologies that improve development speed and system reliability. The Senior Synthetic Data Engineer will design and develop synthetic data, sensor simulation, and world-modeling systems for autonomous-driving networks, while managing large-scale pipelines and debugging cross-stack systems.
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, segmentation, depth, scene semantics, and sensor metadata
- 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, noise modeling, and scenario variation
- Develop Cosmos world model for better world generation, encompassing controllable scenario generation, novel view synthesis, trajectory extrapolation, scene completion, quality triage, regression detection, and controllability evaluation
- 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
Skills
- B.S. or M.S. in Computer Science, Electrical Engineering, Computer Engineering, Applied Math, Physics, or a related field (or equivalent experience)
- 8+ years of experience in computer graphics, computer vision, autonomous driving, sensor simulation, neural rendering, or physically-based sensor modeling, synthetic data generation, or closely related software engineering roles
- Strong Python and C++ skills, with experience building, debugging, profiling, and maintaining production-quality systems on Linux
- Solid mathematical foundation in linear algebra, geometry, probability
- Familiarity with synthetic data annotations, data formats, dataset curation, data augmentation, and evaluation workflows for perception model training and validation
- Familiarity with deep learning workflows and modern ML tooling, with enough practical understanding to translate network needs into synthetic data requirements and measurable quality criteria
- Experience with scalable engineering workflows including Git, Docker, Kubernetes, CI/CD, distributed storage, and deployment in data centers or cloud environments
- Practical experience working directly with NVIDIA NuRec, Cosmos, world foundation models, Real2Sim systems, or autonomous-driving simulation and validation pipelines
- Experience in NuRec world reconstruction, neural rendering, 3D Gaussian Splatting, NeRFs, or occupancy networks
- Deep lidar or radar simulation expertise, such as ray tracing or ray casting, reflectance and intensity modeling, Doppler, radar cross-section, weather effects, occlusion, and sensor-specific noise models
- Experience developing synthetic data pipelines for autonomous driving, closed-loop simulation, domain randomization, long-tail scenario mining, or sim-to-real transfer
- Familiarity with autonomous vehicle data pipelines, OpenDRIVE, HD maps, scenario formats, vehicle dynamics, or AV safety validation
Benefits
- You will also be eligible for equity
Company Overview
Company H1B Sponsorship