4 days ago
Responsibilities
- Build AI-agent workflows that interact with code, compilers, GPU kernels, benchmarks, performance tools, and engineering systems.
- Develop tools for collecting data, running experiments, analyzing feedback, identifying optimization opportunities, and recommending next steps.
- Explore data-driven compiler optimization, GPU-kernel generation and tuning, performance prediction, decision support, and workflow automation.
- Build reliable interfaces between AI agents and compiler, kernel, or developer-tool infrastructure.
- Prototype improvements to compiler flows, code generation, GPU kernels, optimization tools, experimentation systems, or developer workflows.
- Collaborate with compiler, kernel, architecture, AI, and performance engineers on representative workloads.
- Measure correctness, runtime performance, compile time, resource utilization, reliability, and other outcomes.
- Document designs, experiments, results, limitations, and next steps.
Requirements
- Pursuing a BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a similar field.
- Strong programming skills in Python, C, C++, or a similar language.
- Solid foundations in data structures, algorithms, software engineering, and quantitative problem solving.
- Coursework, research, or project experience in one or more of AI, machine learning, AI agents, compilers, programming languages, GPU kernels, CUDA or accelerator programming, systems, performance engineering, optimization, or developer tools.
- Ability to design experiments, analyze results, investigate technical problems, and communicate findings clearly.
- Experience in AI, compiler, kernel, performance, or systems areas, with the ability to learn across technical boundaries.
- Preferred experience includes AI agents, LLM applications, evaluation systems, coding workflows, developer tools, LLVM, MLIR, compiler optimization passes, code generation, domain-specific languages, compiler infrastructure, CUDA, Triton, reinforcement learning, evolutionary algorithms, predictive modeling, ranking, search, or high-dimensional data analysis.
- Research, internships, open-source contributions, or personal projects measuring runtime, compile time, resource use, code quality, or developer productivity are advantageous.
Benefits
- Expected hourly rate is 20 USD–94 USD.
- Eligible for Intern benefits.
- Summer 2027 internship; applications accepted at least until November 6, 2026.
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.