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NVIDIA

Designs the chips and software that power AI

Research and Engineering Intern - Agentic Systems Intelligence

AI ResearchPosted on Nov 5
Internship · Summer 2027$20 - $94 /hrIn-person

About the Job

Requirements

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

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.
  • Collaborate closely with NVIDIA software, model, and hardware teams, with opportunities to bring new capabilities into NVIDIA products.

Desired Qualifications

  • 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; strong engineering and measurable real-world impact are especially valued.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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