Senior / Staff ML Onboard Optimization Engineer
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- Collaborate closely with autonomy and algorithm engineers to scale safe self-driving systems using an AI-first approach.
- Expand the model deployment pipeline to new GPUs and embedded systems for the next generation of our onboard compute system.
- Use frameworks such as TensorRT and modelopt to optimize the models running on the truck.
- Create and benchmark new CUDA kernels for inference.
- Comprehensively profile model runtime and memory to pinpoint performance bottlenecks.
Qualifications:
- MS/PhD or Bachelors degree with a minimum of 6 years of industry experience in Computer Science, Robotics and/or similar technical field(s) of study.
- Solid coding proficiency in a variety of coding languages including Python, C++ or Rust.
- Experience in deep learning frameworks such as PyTorch.
- Skilled in profiling CPU and GPU code using tools such as PyTorch Profiler and NVIDIA Nsight.
- Experience with Nvidia embedded platforms such as Nvidia Jetson or Thor.
- Open-minded and collaborative team player with willingness to help others.
- Passionate about self-driving technologies, solving hard problems, and creating innovative solutions. Bonus/nice to have:
- Experience in model compilation and exporting, interaction with lower level concepts like TensorRT.
- Experience in identifying when custom CUDA kernels are needed, and implementing them.
- Experience in Bazel build systems, and integrating third party packages into dev environments.
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