PhD Research Intern, AI Accelerator Design and VLSI - 2027

AI in this role

pytorch

NVIDIA Research is seeking PhD-level students to work as research interns at the intersection of AI HW/SW Co-Design, Hardware Accelerator Architecture, IC Design Methodology, and VLSI Design. Ideal candidates will have a broad perspective across areas including machine learning fundamentals, quantization and numerical methods for machine learning model optimization, digital VLSI circuits for computer arithmetic, high-productivity VLSI design and verification methodologies including applications of agentic AI to hardware design, AI hardware micro-architecture, and VLSI methodology and implementation.

What You’ll Be Doing:

Accelerator Design: Contribute to novel research advancing the state-of-the-art in the design of accelerators for AI and other high-impact workloads.

VLSI: Research creative and innovative ASIC and VLSI design techniques and/or novel digital VLSI circuits. Apply machine learning, agentic AI, and state-of-the-art tools and methodologies to automated ASIC and VLSI design tool flows.

AI HW/SW Co-Design: Research and develop creative and innovative numerical methods for quantization, sparsity, or tensor decomposition grounded in computer arithmetic fundamentals and digital VLSI circuits.

Collaborate on the development of research prototype testchips.

Collaborate with AI researchers and hardware team members in research and product teams.

Plan to publish and present your original research.

What We Need To See:

Pursuing a PhD in Electrical Engineering, Computer Engineering, Computer Science, or related field.

Publication records in leading ML, architecture, VLSI, or circuits conferences.

Excellent programming skills in Python/PyTorch and hardware design languages such as SystemVerilog/C++; Experience with High-Level Synthesis (HLS) tools is a plus.

VLSI Implementation Skills: Experience in hardware design with proficiency with modern EDA tool flows; Tapeout experience is a plus.

Excellent self-motivation, a high degree of creativity, and a passion for research, collaboration skills, and the ability to work effectively within a research team.

Excellent written and verbal communication skills, with proven experience communicating technical work (e.g., academic presentations, poster sessions); ability to synthesize and explain complex technical concepts.

Widely considered to be one of the technology world’s most desirable employers, NVIDIA has some of the most forward-thinking and hardworking people in the world inventing the future for us. Are you a creative and collaborative researcher interested in seeking new challenges? If so, we want to hear from you!

Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 38 USD - 94 USD.


You will also be eligible for Intern benefits.

Applications for this job will be accepted at least until October 3, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

How we rate this

PhD Research Intern, AI Accelerator Design and VLSI - 2027 at NVIDIA rates 91 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

PyTorch

Questions you could be asked

What's a project where you used PyTorch hands-on?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: PyTorch. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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