AI Computing Software Development Intern - 2027

Overview

• NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years.
• It’s a unique legacy of innovation that’s fueled by great technology and amazing people.
• Today, we’re tapping into the unlimited potential of AI to define the next era of computing.
• An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world.
• Doing what’s never been done before takes vision, innovation, and the world’s best talent.
• As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work.
• Come join the team and see how you can make a lasting impact on the world.
• What You’ll be doing: As an intern, you’ll focus on one of three specialized tracks: TensorRT LLM – Inference Optimization (Python / PyTorch): Build and enhance high‑performance LLM inference pipelines.
• Analyze and optimize model execution, scalability, and memory usage.
• Collaborate across framework and research teams to deliver efficient multi‑GPU model serving.
• TensorRT Compiler – Graph Optimization (C++): Work on the TensorRT compiler backend to improve graph transformations and code generation for NVIDIA GPUs.
• Develop compiler optimization passes, refine operator fusion and memory allocation, and collaborate with CUDA and hardware architecture teams.
• CuTe DSL & CUDA Kernels Development / Optimization (CUDA C++ / Python DSL): Design and tune GPU compute kernels and DSL implementations for core deep learning operations such as GEMM, MoE, Attention and Convolution.
• Profile, analyze and improve CUDA kernel performance to achieve maximum GPU efficiency.
• What We need to see: Pursuing an M.S.
• in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or related field.
• Excellent problem‑solving ability, curiosity for cutting‑edge AI systems, and passion for GPU computing and deep learning software performance.
• TensorRT LLM: Strong Python programming and experience with PyTorch; solid understanding of inference and GPU acceleration.
• TensorRT Compiler: Proficient in C++, with experience in compiler or performance optimization.
• CuTe DSL & CUDA Kernels: Skilled in C/C++ and CUDA or parallel programming; familiar with LLVM, MLIR and compiler; understanding of computer architecture and performance profiling/analysis/optimization.
• Join us and play a part in building the AI computing platforms that drive innovation across industries worldwide.