Performance Engineering Intern, Deep Learning and HPC - 2027

Responsibilities

• Benchmark, profile, and analyze AI and HPC workloads on NVIDIA supercomputers and distributed systems - LLM and VLM training and inference, agentic workloads, world models, and Physical AI for robotics.
• Aggregate and produce written reports with the testing data for internal sales, marketing, SW, and HW teams.
• Build benchmark automation with AI agents and agentic coding tools. Ensure the whole process and results are reliable and reproducible.
• Collaborate with internal teams to debug and resolve performance issues.
• Set up and configure systems with appropriate hardware and software to run benchmarks.
• What we need to see
• Currently pursuing a bachelor's degree (or higher) in Computer Science, Electrical Engineering, or a related field.
• Experienced in programming and debugging with scripting languages such as Python or Unix shell. Hands-on experience with Linux based systems. Familiarity using a container platform such as Docker.
• Fluent with AI coding assistants and agentic workflows, with the judgment to verify what they produce rather than defer to them.
• Hands-on experience with inference frameworks such as TensorRT-LLM, vLLM, or SGLang. Or experience in AI model inference deployment and training.

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