Deep Learning Performance Software Intern - 2027
Listed on NVIDIA’s official careers site. Posted October 1, 2026. Check that it is still open and apply there.
Apply on NVIDIA’s careers site →Job description
We are now looking for a Deep Learning Performance Software Engineering Intern! We are expanding our research and development for deep learning. We seek excellent Software Engineers to join our team. We specialize in developing GPU-accelerated Deep learning software. Researchers around the world are using NVIDIA GPUs to power a revolution in deep learning, enabling breakthroughs in numerous areas. Join the team that builds software to enable new solutions.
Your ability to work in a fast-paced customer-oriented team is required and excellent communication skills are necessary.
What you’ll be doing
Creating and maintaining SKILL, Wiki, and agent harness Develop TileGym , Triton CUDA TileIR backend and CUDA Tile Develop highly optimized deep learning kernels through tile-based GPU programming model End-to-end performance optimization through tile-based GPU programming model Do performance optimization, analysis, and tuning What we need to see: Pursuing a degree from a university in an engineering or computer science related field.
A masters or doctoral candidate is preferred. Understands the core components of agentic systems, including LLM APIs, prompting, tool use/function calling, agent loops, planning, reasoning, memory, RAG, skills, MCP, sub-agents, multi-agent architectures, context engineering, and harness engineering. Excellent C/C++ programming and software design skills Python experience a plus MLIR experience a plus Performance modelling, profiling, debug, and code optimization or architectural knowledge of CPU and GPU GPU programming experience (CUDA or OpenCL) desired NVIDIA is widely considered to be one of the technology world’s most desirable employers.
We have some of the most brilliant and talented people on the planet working for us. If you're creative and autonomous, we want to hear from you!
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