Research Scientist, Electronic Design Automation - New College Grad 2026
Company websitenvidia.com (NVIDIA, opens in new tab)
Base salary $168,000 to $264,500
Employer-published annual base salary, USD. Advertised base range in Santa Clara, CA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSanta Clara, CA
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (1 h ago) · observed since
About this job
NVIDIA Research is searching for a world-class new college grad PhD researcher to drive groundbreaking research at the intersection of AI, GPU computing, and Electronic Design Automation (EDA). Deep learning and GPU acceleration are transforming the future of chip design, and this role offers the opportunity to shape that future. 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!
What you'll be doing:
Define and conduct original research across EDA algorithms, VLSI design methodology, and advanced AI techniques.
Innovate in EDA software and algorithms, with applications spanning supervised, unsupervised, reinforcement learning, agentic AI systems, as well as GPU-accelerated optimization methods.
Apply deep learning and GPU computing to improve ASIC and VLSI design tool flows.
Collaborate cross-functionally with circuit design, VLSI, and architecture teams, ensuring research translates into real-world product impact.
Publish and present your original research, speak at conferences and events
Collaborate with external researchers and a diverse set of internal product teams.
What we need to see:
PhD in Computer Science, Electrical/Computer Engineering, or related field (or equivalent experience)
Strong Programming & Systems Skills: Proficiency in at least two of Python, PyTorch, C++, or CUDA
Publications in top EDA and AI/ML venues
Domain & Technical Expertise: Expertise in EDA (e.g., synthesis, physical design, design verification, timing) algorithms combined with publications and project experience applying machine learning/deep learning (supervised, unsupervised, RL, agentic AI) to impactful problems.
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.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 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.Source: NVIDIA on Workday · View original posting (opens in new tab)
Pay in context
This role's base floor ($168,000) is above 32% of the 1,729 Data & ML roles in California listed on this site; 12 others list the same floor. Their median floor is $184,000; the middle half runs from $154,000 to $224,000.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 8, 2026.
This listingResearch Scientist, Electronic Design Automation - New College Grad 2026$168,000 to $264,500
L11 System Product Development Engineer$168,000 to $258,750
Senior Software Engineer, Network Visibility Platform - DGX Cloud$168K to $322K
Hardware Validation Procedures and Documentation Lead$168,000 to $258,750
Senior Software Engineer, Platform Engineering$168K to $322K
PhD Research Scientist, Fundamental Generative AI - New College Grad 2026$168,000 to $264,500
AI Engineering Manager - Finance$168K to $322K
Chart as a table
| Role | Published base |
|---|---|
| Research Scientist, Electronic Design Automation - New College Grad 2026 (this listing) | $168,000 - $264,500 |
| L11 System Product Development Engineer | $168,000 - $258,750 |
| Senior Software Engineer, Network Visibility Platform - DGX Cloud | $168K - $322K |
| Hardware Validation Procedures and Documentation Lead | $168,000 - $258,750 |
| Senior Software Engineer, Platform Engineering | $168K - $322K |
| PhD Research Scientist, Fundamental Generative AI - New College Grad 2026 | $168,000 - $264,500 |
| AI Engineering Manager - Finance | $168K - $322K |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-10-30
Where this pay comes from
Location as the employer wrote it: US, CA, Santa Clara
base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 168,000 USD – 264,500 USD.
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
