NVIDIA

NVIDIA

Posted via Workday

Senior Synthetic Data Engineer - Autonomous Driving

Posted Sep 21, 2026

Role at a glance

Job function
AI & Data Data Engineering
Salary
$184K – $356.5K/yr
Location
Santa Clara, California, United States
Work arrangement
On-site
Employment
Full-time
Experience
8+ years of experience
Education
B.S. or M.S. in Computer Science, Electrical Engineering, Computer Engineering, Applied Math, Physics, or a related field (or equivalent...

Spotted an issue?

We’ll check it against the original posting.

Log in to report

Role Summary

AI-generated

The Senior Synthetic Data Engineer will join NVIDIA's DRIVE team to design and develop simulation environments for autonomous-vehicle technology. The role focuses on synthetic data generation, sensor simulation, and Cosmos world models using NuRec reconstructed worlds and Cosmos-generated environments.

What You'll Do

  • Build, implement, and optimize tools to generate synthetic data for DRIVE deep learning networks.
  • Develop lidar and radar sensor simulation workflows for NuRec reconstructed driving worlds and Cosmos-generated environments.
  • Develop Cosmos world models for controllable scenario generation, novel view synthesis, trajectory extrapolation, scene completion, and...
  • Collect perception, planning, and deep learning network requirements and develop tools to address synthetic-data and sensor-simulation gaps.
  • Develop dataset quality assessments and synthetic-real comparison procedures.
  • Set up, profile, and supervise large-scale NuRec, Cosmos, and sensor simulation pipelines in data center or cloud environments.

Generated from the employer's posting. Verify important details before applying.

View full posting

Qualifications

Required: 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, physically-based sensor modeling, synthetic data generation, or closely related software engineering roles; strong Python and C++ skills; production-quality systems experience on Linux; mathematical foundation in linear algebra, geometry, and probability; familiarity with synthetic data annotations, data formats, dataset curation, data augmentation, evaluation workflows, deep learning workflows, modern ML tooling, Git, Docker, Kubernetes, CI/CD, distributed storage, and deployment in data centers or cloud environments.

Required

  • B.S. or M.S. in Computer Science, Electrical Engineering, Computer Engineering, Applied Math, Physics, or a related field (or equivalent...
  • 8+ years of experience in computer graphics, computer vision, autonomous driving, sensor simulation, neural rendering, or...
  • Strong Python and C++ skills
  • 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...
  • Familiarity with deep learning workflows and modern ML tooling
  • Experience with scalable engineering workflows including Git, Docker, Kubernetes, CI/CD, distributed storage, and deployment in data...

Preferred

  • Practical experience working directly with NVIDIA NuRec, Cosmos, world foundation models, Real2Sim systems, or autonomous-driving...
  • Experience in NuRec world reconstruction, neural rendering, 3D Gaussian Splatting, NeRFs, or occupancy networks
  • Deep lidar or radar simulation expertise
  • Experience developing synthetic data pipelines for autonomous driving, closed-loop simulation, domain randomization, long-tail scenario...
  • Familiarity with autonomous vehicle data pipelines, OpenDRIVE, HD maps, scenario formats, vehicle dynamics, or AV safety validation

Original job description

Content provided by the employer

Autonomous vehicles are redefining the way we live, work, and play—creating safer and more efficient roads. These ground-breaking benefits require substantial computational horsepower and large-scale production software expertise. Tapping into decades-long experience in high-performance computing, imaging, and AI, 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. It delivers everything needed to develop autonomous vehicles at scale.

Simulation allows us to test an autonomous vehicle in nearly infinite conditions and scenarios. This happens before the vehicle reaches the road. It speeds up development and improves the system's reliability. NVIDIA Omniverse NuRec and Cosmos are starting a new chapter for autonomous-driving simulation. NuRec converts real-world sensor data into high-fidelity, simulation-ready driving environments. Cosmos world models generate, complete, and evaluate dynamic driving scenes, novel viewpoints, long-tail trajectories, and controlled scenario variations beyond the original sensor path. We seek a Senior Synthetic Data Engineer to join the NVIDIA DRIVE team and contribute to automotive innovation. In this important role, you will collaborate with technical leaders in autonomous driving, NuRec, Cosmos, and sensor simulation. Together, you will design and develop a simulation environment that pushes forward autonomous vehicle technology.

What you'll be doing:

  • 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.

What we need to see:

  • 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.

Ways to stand out from the crowd:

  • 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.

#AutonomousVehicles

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 25, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

NVIDIA

About the company

NVIDIA

Large Enterprise

NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.