Research Scientist, AI Accelerator Design and VLSI - New College Grad 2026

About the Role

NVIDIA Research is seeking a world-class new college grad PhD researcher to drive groundbreaking research at the intersection of AI HW/SW Co-Design, AI Hardware Accelerator Architecture, IC Design Methodology, and VLSI Design. Ideal candidates will have a 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 generative AI to hardware design, AI hardware micro-architecture, and VLSI methodology and implementation.

What you'll be doing:

• AI Accelerator Hardware: Contribute to novel research advancing the state-of-the-art in AI accelerator design.
• VLSI: Research creative and innovative ASIC and VLSI design techniques and/or novel digital VLSI circuits. Apply machine learning, generative AI, and innovative 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.
• Publish and present your original research, speak at conferences and events.

What we need to see:

• PhD in Computer Science, Electrical/Computer Engineering, or related field (or equivalent experience).
• VLSI Implementation Skills: Experience in hardware design with proficiency with modern EDA tool flows.
• Programming & Systems Skills: Proficiency in at least two of Python, PyTorch, C++, SystemVerilog, or CUDA.
• Publications in top circuit, architecture, and/or AI/ML venues.
• Domain & Technical Expertise: PhD research experience in either VLSI (e.g., digital VLSI circuits and chip design methodologies), computer architecture, and/or numerical algorithms for AI model HW/SW co-design.
• 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.