NVIDIA end-to-end network management solutions enable monitoring, management, analytics and visibility. Backed by Sequoia.
About the role
Self-driving cars need to understand the road ahead in real time, even without a prior map. Our team builds the online mapping system that turns raw data from multiple sensors into an accurate, continuously updated 3D model of the driving environment. This model captures lanes, road boundaries, crosswalks, intersection layouts, and traffic control information to support decisions across the autonomous driving system. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Learned mapping involves training DNNs to predict map elements directly from visual sensors, laser scanning, and radar. This includes owning the GT story and collaborating with partners to provide the vital data
- Geometry and C++ engineering: building the post-processing that turns network outputs into stable, consistent, production-ready map elements
- Design, train, and improve PyTorch models that predict online map elements (lanes, road boundaries, crosswalks, road markings, topology) from camera, LiDAR, and/or radar, using BEV and vectorized-map representations
- Write production C++ for geometry-based post-processing: curve and surface fitting, association, multi-frame fusion and tracking, topology reasoning, and consistency checks on DNN outputs
- Apply multi-view geometry, calibration, coordinate transforms, and sensor fusion to produce 3D maps that stay accurate and stable over time
- Optimize and deploy models alongside algorithms on NVIDIA DRIVE Orin and Thor under real-time and safety constraints, and get them running in vehicles
More about this role
Self-driving cars need to understand the road ahead in real time, even without a prior map. Our team builds the online mapping system that turns raw data from multiple sensors into an accurate, continuously updated 3D model of the driving environment. This model captures lanes, road boundaries, crosswalks, intersection layouts, and traffic control information to support decisions across the autonomous driving system. You’ll write the models, write the C++, and ship both into vehicles on the road, running on NVIDIA DRIVE Orin and Thor. The tasks you perform will be tested at scale, on real cars, with real safety requirements. NVIDIA’s autonomous driving stack spans the full range of automation, and online mapping is a core component across it, so your work will reach L2++, L3, and L4 systems. The role spans two subject areas, and we want someone who enjoys both:
- Learned mapping involves training DNNs to predict map elements directly from visual sensors, laser scanning, and radar. This includes owning the GT story and collaborating with partners to provide the vital data.
- Geometry and C++ engineering: building the post-processing that turns network outputs into stable,...
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