Autonomous vehicles are redefining the way we live, work, and play—creating safer and more efficient roads and these revolutionary benefits require massive 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 continuous deployment through over the air updates. It delivers everything needed to develop autonomous vehicles at scale. Simulation gives us the capability to test an autonomous vehicle in a near-infinite variety of conditions and scenarios before it even reaches the road, accelerating development time and improving the reliability of the self-driving stack at the same time. With DRIVE Sim 2.0, NVIDIA is writing a new chapter on real-time simulation. Built on our Omniverse platform and harnessing the power of RTX ray tracing, we're revolutionizing the world of simulation, combining enterprise-grade simulation with entertainment-quality graphics. We're looking for a Synthetic Data Generation Tool Engineer to join the DRIVE Sim team and help us make automotive history. This meaningful role will see you working with technical visionaries within the company to define and deliver a simulation environment that advances the state of the art in autonomous vehicles.What you’ll be doing: Design and implement different DRIVE Sim tools to generate synthetic data (RGBD, segmentation, bounding boxes, point clouds). Implement different algorithms to convert these raytraced sensor data to different novel ground truths (free space around vehicles, occupancy voxels, etc.) for different deep learning DRIVE networks. Optimize the above algorithms for best performance on different GPUs, cloud and local platforms. Work closely with runtime, sensor, Omniverse teams to implement those tools and algorithms.Participate in the large-scale deployment in the data center of DRIVE Sim and its supporting tools. Ensures transfer learning from simulation training results to real world inferencing. What we need to see: Bachelor degree in Computer Science or related field or equivalent experience8+ years of experience or equivalent training.Proficiency with C++/Python. Strong mathematical fundamentals, including linear algebra and calculus.Understanding of memory management, multiple processor use, and runtime optimization. Prior experience with game/physics engine development, code optimization.Ways to stand out from the crowd: Experience with Synthetic Data Generation. Experience with OpenDRIVE, physics simulation software, sensor simulation, computer graphics, raytracing, version control. Familiar with AI concepts: Supervised Learning, Reinforcement Learning. Background with Docker, Scalable Cloud, AWS, Kubernetes deployments. Experience with Universal Scene Description (USD)The base salary range is 135,000 CAD - 292,500 CAD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
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