XPENG
Smart Technology
AIInfraOnboardPerformanceIntern
Neural analysis suggests this role is
optimal for Mid+ candidates.
“AI Infra Onboard Performance Intern at XPENG. Skills: AI model deployment, Performance optimization. Design software for deploying AI models. Optimize software for AI models”
What You'll Achieve.
Scale optimizations across vehicle fleet
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
Master's or PhD in CS/CE/EE, Relevant industry or research experience, Expertise in C++, Expertise in Python, Performance-sensitive code, Production-quality code, In-depth understanding of computer architecture, In-depth understanding of high-performance computing, Proven experience in application performance analysis, Proven experience in optimization, Experience using profiling tools
Nice to Have
Experience writing CPU kernels, Experience writing CUDA kernels, Experience optimizing CPU kernels, Experience optimizing CUDA kernels, Experience developing performance tooling, Experience developing instrumentation, Familiarity with embedded compute platforms, Familiarity with automotive compute platforms, Familiarity with power constraints, Familiarity with thermal constraints, Previous experience in autonomous driving, Previous experience in robotics
What You'll Do.
Design software for deploying AI models
Optimize software for AI models
Profile inference performance
Improve inference performance
Improve power efficiency
Deliver production-ready optimizations
How You'll Work.
Team & Collaboration
Cross-functional teams
Full Job Description
XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity. 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: 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
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