Research and Engineering Intern, Agentic Systems Intelligence – Summer 2027

at Nvidia

USD 20-94 per hour

INTERN

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 6 Agentic AI @ 6 Agentic Systems CUDA Data Pipelines Experimentation GPU @ 3 HPC LLM @ 3 Machine Learning @ 6 Performance Optimization @ 3 Python @ 6 Reinforcement Learning @ 6 Rust @ 6 SGLang @ 3 vLLM @ 3

Details

NVIDIA's Agentic Systems Intelligence (ASI) team is seeking a Research and Engineering Intern to help advance high-performance, agentic AI systems for the CUDA ecosystem. The team works across the full stack, including model training and improvement, agent architectures, multi-agent systems, systems, runtimes, and evaluation frameworks.

The role involves investigating open-ended research questions and turning promising ideas into working systems that can reason about, generate, optimize, and operate across NVIDIA's accelerated computing stack. Depending on interests and strengths, work may focus on model and agent capabilities, scalable agent systems and runtimes, or high-fidelity training and evaluation environments. The intern will collaborate with NVIDIA software, model, and hardware teams and may contribute new capabilities to NVIDIA products.

Responsibilities

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.

Requirements

Pursuing a master's degree or PhD in Computer Science, Electrical Engineering, or a similar field.
Strong foundations in one or more of 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.

Preferred Qualifications

PhD research in a relevant area, with the 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.
Technical depth and ownership demonstrated through impactful research prototypes, deployed systems, or substantial open-source contributions.
Relevant publications are welcome; strong engineering and measurable real-world impact are especially valued.

Benefits

Competitive compensation.
Intern benefits.
NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer.
Applications will be accepted at least until November 9, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.