Research and Engineering Intern, Agentic Systems Intelligence - Summer

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 30 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.

We are looking for an outstanding Research & Engineering Intern to join NVIDIA’s Agentic Systems Intelligence (ASI) team, a frontier research and engineering team advancing high-performance AI. Our team builds the next generation of agentic AI systems for the CUDA ecosystem, working across the full stack—from training and improving models, to designing agent architectures and multi-agent systems, to building the systems, runtimes, and evaluation frameworks that make them effective at scale.

You will investigate open-ended research questions and turn promising ideas into working systems that can reason about, generate, optimize, and operate across NVIDIA’s accelerated computing stack. Depending on your strengths and interests, your work may focus on advancing model and agent capabilities, building scalable agent systems and runtimes, or developing high-fidelity training and evaluation environments.

You will collaborate closely with NVIDIA software, model, and hardware teams, with opportunities to bring new capabilities into NVIDIA products.

• Research, build, and optimize agentic AI systems for the CUDA ecosystem, including agent architectures, multi-agent workflows, tool use, memory, and orchestration.
• Develop data pipelines, environments, verification tools, reward mechanisms, and evaluation frameworks to improve model and agent capabilities through rigorous experimentation.
• Co-design and optimize agentic systems across NVIDIA’s software and hardware stack, connecting advances in models and agents with compilers, runtimes, libraries, kernels, and GPUs.
• Demonstrate measurable improvements in correctness, performance, or developer productivity.

• You are pursuing a Master’s, or PhD in Computer Science, Electrical Engineering, or a similar field.
• Strong foundations in one or more of the following: AI systems, agentic AI, machine learning, reinforcement learning, high-performance computing, or computer architecture.
• Hands-on research or development experience in agent systems, coding agents, model training, reinforcement learning, or modern AI inference systems.
• Strong Python programming skills and proficiency in C/C++ or Rust, with solid software engineering fundamentals.
• Experience with GPU computing and an interest in performance optimization and working across system boundaries.

• PhD research in a relevant area, with demonstrated ability to formulate research questions, build working implementations, and evaluate them rigorously.
• Experience building coding agents, autonomous software-engineering systems, or agent training and evaluation environments.
• Hands-on experience with GPU programming and performance optimization, or with systems such as TRT-LLM, SGLang, or vLLM.
• Evidence of technical depth and ownership through impactful research prototypes, deployed systems, or substantial open-source contributions.
• Relevant publications are welcome; we especially value strong engineering and measurable real-world impact.

With competitive salaries and a…