
10,000+ employees
Founded 1993
🏥 Healthcare
🏭 Manufacturing
🤖 Artificial Intelligence
Healthcare • Manufacturing • Artificial Intelligence
NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.
🔥 14 hours ago
🏄 California, New York, +2 more states – Remote
💵 $184k - $356.5k / year
⏰ Full Time
🟠 Senior
🚰 Data Engineer
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10,000+ employees
Founded 1993
🏥 Healthcare
🏭 Manufacturing
🤖 Artificial Intelligence
Healthcare • Manufacturing • Artificial Intelligence
NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.
• Build, implement, and optimize tools to generate synthetic data for training 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, quality triage, regression detection, and controllability evaluation • Gather perception, planning, and deep learning network requirements and align them with synthetic data and sensor simulation capabilities • Develop new tools and improve performance where capability gaps exist • Develop dataset quality assessments and synthetic-real comparison procedures • Evaluate sensor realism, annotation quality, distribution coverage, scenario diversity, and sim-to-real transfer • Set up, profile, and supervise large-scale NuRec, Cosmos, and sensor simulation pipelines in data center or cloud environments • Debug systems spanning sensors, reconstruction models, world models, simulation runtime, GPU workloads, distributed data services, and autonomous-driving workloads • Collaborate with technical leaders in autonomous driving, NuRec, Cosmos, and sensor simulation
• 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 • 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 ML tooling • Practical understanding sufficient to translate network needs into synthetic data requirements and measurable quality criteria • Experience with Git, Docker, Kubernetes, CI/CD, distributed storage, and deployment in data centers or cloud environments • Practical experience with NVIDIA NuRec, Cosmos, world foundation models, Real2Sim systems, or autonomous-driving simulation and validation pipelines is advantageous • Experience in NuRec world reconstruction, neural rendering, 3D Gaussian Splatting, NeRFs, or occupancy networks is advantageous • Deep lidar or radar simulation expertise is advantageous • Experience developing synthetic data pipelines for autonomous driving, closed-loop simulation, domain randomization, long-tail scenario mining, or sim-to-real transfer is advantageous • Familiarity with autonomous vehicle data pipelines, OpenDRIVE, HD maps, scenario formats, vehicle dynamics, or AV safety validation is advantageous
• Equity • Benefits
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