Solutions Architecture Intern - Summer 2027

at Nvidia

USD 20-71 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 @ 3 Agentic AI CUDA @ 2 Communication @ 3 Data Science @ 3 Debugging Docker @ 2 GPU @ 3 InfiniBand JAX @ 2 Kubernetes @ 2 LLM Linux @ 2 Machine Learning @ 3 Mathematics @ 3 Networking @ 3 PyTorch @ 2 Python @ 6 Reinforcement Learning @ 2 Robotics @ 2 Slurm @ 2 System Administration @ 3

Details

NVIDIA Solution Architects help partners and customers succeed with new NVIDIA technologies. In this internship, you will work with experienced Solution Architects across the full stack. Projects may involve infrastructure, robotics, agentic AI, machine learning, and related technologies.

Responsibilities

Collaborate with solution architects, engineering teams, and product teams.
Understand the technical needs of partners and customers.
Develop proof-of-concept projects using NVIDIA technologies.
Work on projects involving AI infrastructure, machine learning, robotics, networking, cloud infrastructure, workload orchestration, and AI models.
Depending on the internship area, contribute to cluster monitoring and telemetry, utilization and reliability tracking, infrastructure automation, network troubleshooting, packet-level debugging, InfiniBand or RoCE fabric tuning, AI workload optimization, inference platforms, robotics pipelines, sensor processing, or digital twins.
Engage with engineering, product, and business development teams to help partners leverage NVIDIA technologies for training, fine-tuning, inference, retrieval, and agentic workloads.

Requirements

Pursuing a BS, MS, or PhD in Computer Architecture, Computer Networking, Computer or Electrical Engineering, Computer Science, Mathematics, Physics, Data Science, or a related technical field.
Strong skills in one or more programming languages, such as Python, C, or C++.
Excellent presentation, communication, and teamwork skills.
Ability to work independently and with cross-functional teams.
Comfortable multitasking in a fast-paced environment with changing requirements.
Strong analytical and problem-solving skills.
Curiosity about AI infrastructure and the modern AI stack, including LLMs, inference serving, agentic workloads, and retrieval workloads, is a plus.

Preferred Qualifications

Experience with NVIDIA GPUs and software libraries.
Engineering or research community experience.
Foundations in computer architecture, networking, data science, or machine learning, along with Linux skills.
System administration or hands-on server and rack-level hardware experience.
Experience with workload orchestration, data center infrastructure, or AI Factory deployments.
Familiarity with GPUs, AI, CUDA, Linux, Python, Slurm, Docker, Kubernetes, PyTorch, JAX, inference-serving frameworks, or agentic frameworks.
Knowledge of data center architectures, L2-L7 networking, leaf-spine topologies, RDMA, RoCE, on-premises and cloud infrastructure, and GPU clustering.
For robotics-focused work: familiarity with reinforcement learning, vision-language-action models, motion planning, physics-based simulation, software-in-the-loop testing, ROS, Isaac Sim, synthetic data generation, and robotics foundation models.
For sensor-processing work: interest or experience in geospatial, signal, radar, RF processing, multimodal sensor fusion, digital twins, and high-performance sensor systems.

Internship Areas

This posting represents multiple Solutions Architecture Internships in Santa Clara, California, including:

AI Factory Deployment
AI Factory / AI Cloud
AI Factory Networking
AI Factory Operations
AI Models and AI Agents
Robotics / Physical AI
Sensor Processing

The internship is full time. Applications will be accepted at least until September 15, 2026. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.