About the role
Key Responsibilities
- Design and optimize software for deploying large-scale AI models in production vehicles.
- Profile and improve inference performance across compute, memory, and I/O systems.
- Reduce latency and improve power efficiency on embedded automotive platforms.
- Deliver production-ready optimizations that scale reliably across the vehicle fleet.
Basic Qualifications
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Master's or PhD in CS/CE/EE or equivalent, with relevant industry or research experience.
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Strong expertise in C++ and Python, including performance-sensitive, production-quality code.
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In-depth understanding of computer architecture and high-performance computing (memory hierarchy, parallelism, vectorization, scheduling).
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Proven experience in application performance analysis and optimization, using profiling tools to diagnose and resolve bottlenecks.
Preferred Qualifications
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Experience writing and optimizing CPU or CUDA kernels.
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Experience developing performance tooling and instrumentation (e.g., eBPF, perf, custom tracing/profiling frameworks) for production or embedded systems.
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Familiarity with embedded or automotive compute platforms (e.g., NVIDIA Orin, Drive) and their power/thermal constraints.
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Previous experience in the autonomous driving or robotics industry.
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Effective at solving complex problems collaboratively within larger cross-functional teams.
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A fun, supportive and engaging environment.
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Infrastructures and computational resources to support your work.
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Opportunity to work on cutting edge technologies with the top talents in the field.
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Opportunity to make significant impact on the transportation revolution by the means of advancing autonomous driving.
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Competitive compensation package.
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Snacks, lunches, dinners, and fun activities.