Senior Synthetic Data Engineer - Autonomous Driving

Details

Autonomous vehicles are redefining the way we live, work, and play by creating safer and more efficient roads. NVIDIA has built a software-defined, end-to-end platform for the transportation industry that enables continuous improvement and deployment through over-the-air updates.

Simulation allows autonomous vehicles to be tested in nearly infinite conditions and scenarios before reaching the road. NVIDIA Omniverse NuRec converts real-world sensor data into high-fidelity, simulation-ready driving environments, while Cosmos world models generate, complete, and evaluate dynamic driving scenes, novel viewpoints, long-tail trajectories, and controlled scenario variations.

The Senior Synthetic Data Engineer will join the NVIDIA DRIVE team and collaborate with technical leaders in autonomous driving, NuRec, Cosmos, and sensor simulation to design and develop simulation environments for autonomous vehicle technology.

Responsibilities

• Build, implement, and optimize tools to generate synthetic data for training 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 models for improved world generation, including 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 identified.
• 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.

Requirements

• Bachelor's or master's degree in Computer Science, Electrical Engineering, Computer Engineering, Applied Mathematics, Physics, or a related field, or equivalent experience.
• At least 8 years of experience in computer graphics, computer vision, autonomous driving, sensor simulation, neural rendering, 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, and 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 machine learning 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.

Preferred Qualifications

• Practical experience 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 autonomous vehicle safety validation.

Compensation and Benefits

The base salary range is USD 184,000–287,500 for Level 4 and USD 224,000–356,500 for Level 5. Base salary is determined based on location, experience, and the pay of employees in similar positions. The role is also eligible for equity and benefits.

Applications will be accepted at least until September 25, 2026. NVIDIA is an equal opportunity employer committed to fostering an inclusive work environment.