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XPENG · 3 weeks ago

GPGPU Software Architect/ Principal Engineer

Santa Clara, CA

Full-time

Onsite

Lead/Staff

$242K/yr - $409K/yr

10+ years exp

XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles. The role involves developing a comprehensive software stack compatible with CUDA and overseeing the architecture and design for GPU technologies.

AutomotiveAutonomous VehiclesElectric VehicleManufacturing

Hiring Manager

Yuqing Wang, SHRM-CP

Responsibilities

Develop and refine a comprehensive 3-year roadmap for a software stack compatible with CUDA, encompassing Runtime, Driver, Compiler, Profiler, Debugger, and AI acceleration libraries

Define binding specifications that link our upcoming GPU ISA to CUDA APIs, ensuring forward compatibility with CUDA 12.x features

Evaluate and integrate the latest technological advancements: CUDA Graph, Transformer Engine, virtual memory management, CUDA dynamic CUTLASS 3.x, TMA, Blackwell FP4, among others

Create a modular, layered Runtime architecture: CUDA → HAL → Kernel → Hardware, applicable across emulators, and actual silicon

Define the task launch protocol, including Queue, Stream, Event, and Graph, as well as the memory model

Design a dual-mode (JIT & offline) compiler supporting LTO, PGO, Auto-Tuning, and efficient PTX→ISA microcode caching

Develop GPU virtualization schemes(MIG) that work across processes and containers

Implement an end-to-end performance model: Python API → CUDA Runtime → Driver → ISA → Micro-architecture → Board-level interconnect

Build an observability platform: Nsys-compatible traces, real-time Metric-QPS dashboards, and an AI Advisor for identifying bottlenecks automatically

Manage internal AI benchmarks as the single source of truth. Benchmark includes MLPerf Inference, Stable Diffusion XL, and 70B LLM

Co-design ISA which compatible with CUDA Compute Capability 12.x with our hardware architecture team

Collaborate with AI framework teams (PyTorch, TensorFlow, JAX, ONNX Runtime) to build fully reusable kernel libraries

Partner with Cloud and K8s teams to co-develop Device Plugins, GPU Operators, and RDMA Network Policies

Qualification

CUDAGPU architectureAI acceleration librariesPTX/SASSPCIe/CXL/RDMALLVM NVPTXPerformance modelingObservability platformCross-functional collaboration

Required

10 years + in systems software, with at least 5 years in designing CUDA Compute stacks

Led end-to-end development of a GPU Runtime or AI acceleration library generation

Comprehensive mastery of PTX/SASS, CUDA Driver API, and cuBLAS/cuDNN internals; experience with LLVM NVPTX backend

Profound understanding of GPU micro-architecture, including SM architecture, Warp Scheduler, Shared-Memory conflicts, and Tensor Core pipelines

Proficiency with PCIe/CXL/RDMA topologies, NUMA settings, and GPU Direct RDMA/Storage

Benefits

Bonus

Equity

Benefits

Company

XPENG

Glassdoor2.8

XPeng is a leading Chinese Smart EV company that designs, develops, manufactures, and markets Smart EVs that appeal to the large and growing base of technology-savvy middle-class consumers.

Founded in 2014

Guangzhou, Guangdong, CHN

10001+ employees