Imagine being able to test a self-driving vehicle computer in high-fidelity real-time simulation – feeding it everything the real car and its sensors would see, as well as responding in real-time to the self-driving computer’s actions. NVIDIA is making it happen, enabling the industry to drive billions of miles in real-time simulation with the powerful new NVIDIA DRIVE Constellation AV simulator. DRIVE Constellation applies physically-based and real-time sensor simulation and the computing horsepower of two different servers to deliver a groundbreaking cloud-based testing platform for autonomous driving.
Visualize solving hard problems including real-time Camera/Radar/Lidar sensor modeling, deterministic scheduling and synchronization in a parallel/distributed, real-time vehicle and vehicle dynamics modeling, parallel and distributed CPU and GPU processing, traffic / driver / pedestrian behavior modeling, scenario scheduling and execution, and many others!
What you’ll be doing:
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As a member of the DRIVE Sim development team, you will work on the simulation framework that supports sensor models, vehicle dynamics and networking.
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Develop the APIs and system software that enable high-throughput, low-latency data flow.
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Build easy-to-use user interface components that enable a coherent authoring and model characterization workflow.
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Collaborate with a global, diverse team of engineers encompassing the entire NVIDIA Automotive and Developer Technology platforms.
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Requires strong communication skills and should have a track record of working well within a team and working well across organizations.
What we need to see:
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BS, MS, or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or related technical discipline and 3+ years relevant experience
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Excellence in C++ software development and proven experience building complex software systems.
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Excellent skills in system software, for example OS fundamentals, networking and embedded real-time systems.
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Familiarity with embedded platforms, and/or real-time systems.
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Demonstrated capability in professional software engineering practices, including coding standards, code reviews, source control management, build processes, testing, and operations.
Ways to stand out from the crowd:
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FAA-approved commercial aviation flight simulators.
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Real-time and/or distributed systems.
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Sensor modeling (Camera, Radar, Lidar).
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Vehicle and physics modeling and simulation.
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Experience in applying data science methods.
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Pertinent Automotive experience (e.g. ADAS system verification, autonomous driving SW development, traffic modeling, etc).
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GPU graphics and compute programming (e.g. Vulkan, CUDA, Raytracing, OptiX, Blender