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