20 hours ago
Shanghai, ChinaIntern
Responsibilities
- Contribute to production-quality AI software, including deep learning libraries, GPU kernels, and LLM inference infrastructure.
- Design, implement, optimize, and tune GPU kernels and performance primitives for AI workloads.
- Build software abstractions for deep learning libraries, LLM serving engines, and runtime systems.
- Contribute to just-in-time compilation, code generation, and runtime technologies.
- Analyze workload performance and propose improvements to software and hardware-software interfaces.
- Collaborate with deep learning, compiler, library, kernel, and GPU architecture teams.
- Contribute to relevant open-source projects and ecosystem integrations.
Requirements
- Currently pursuing a bachelor’s, master’s, or PhD degree in Computer Science, Electrical Engineering, or a related field.
- Coursework, research, or project experience in machine learning, deep learning systems, compilers, systems software, or GPU programming.
- Strong programming skills in C/C++ and Python.
- Familiarity with CUDA and GPU programming fundamentals.
- Experience with deep learning frameworks such as PyTorch, JAX, TensorFlow, or ONNX.
- Understanding of linear algebra, performance analysis, profiling, and code optimization.
- Interest in software abstractions, APIs, performance-sensitive system architecture, and modern ML inference trends.
- Strong problem-solving, curiosity, and collaboration skills.
- Preferred experience includes vLLM, SGLang, MLC, TensorRT-LLM, MLIR, Apache TVM, TensorIR, GPU performance modeling, computer architecture, accelerator software design, or meaningful open-source contributions.
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.