5 months ago
Santa Clara, CA, USAIntern
H1B sponsor
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.
- Collaborate effectively on complex problems within larger cross-functional teams.
Requirements
- Master's or PhD in computer science, computer engineering, electrical engineering, 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, including memory hierarchy, parallelism, vectorization, and scheduling.
- Experience analyzing and optimizing application performance with profiling tools to diagnose and resolve bottlenecks.
- Preferred: experience writing and optimizing CPU or CUDA kernels.
- Preferred: experience developing performance tooling and instrumentation such as eBPF, perf, and custom tracing or profiling frameworks.
- Preferred: familiarity with embedded or automotive compute platforms such as NVIDIA Orin and Drive, including power and thermal constraints.
- Preferred: previous experience in the autonomous driving or robotics industry.
Benefits
- Supportive and engaging work environment
- Infrastructure and computational resources to support the work
- Opportunity to work with cutting-edge technologies and leading talent
- Snacks, lunches, dinners, and fun activities
Categories
About XPENG
XPENG designs, manufactures, and sells smart electric vehicles for consumers, integrating in-house advanced driver-assistance systems and connected in-car software. Founded in 2014 and headquartered in Guangzhou, it operates plants in Zhaoqing and Guangzhou, maintains a European HQ in Amsterdam, and develops eVTOL aircraft via XPENG AEROHT.