AI Infra Onboard Performance Intern

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.

What do we provide:

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.