Research Scientist, Fundamental Generative AI - 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 (9 min ago) · observed since
About this job
NVIDIA is searching for a world-class generative AI researcher to join the fundamental generative AI research team at NVIDIA Research. We strive for research that pushes boundaries and builds the next generation of generative models but also has an impact on the world. We are interested in advancing generative AI methods for biomolecular design, including small molecule, protein, and RNA design, as well as other scientific applications (i.e., GenAI4Science). You are expected to have a strong mathematical foundation and be capable of analyzing and developing novel models. The position will focus on fundamental research, with the freedom and bandwidth to conduct ground-breaking research. You will work within an amazing and collaborative research team that consistently publishes at the top venues in machine learning and AI for science. You will be empowered to make contributions that create real-world impact.
What you'll be doing:
Research, design, and implement novel, large-scale generative AI methods.
Publish original research.
Collaborate with team members, research teams, as well as product teams.
Speak at conferences and events.
Transfer technology to product groups.
What we need to see:
Completing or recently completed a Ph.D. in Computer Science/Engineering, Statistics, etc. (or equivalent experience)
Excellent knowledge of the theory and practice of generative AI.
Experience in building generative models for molecules, molecular dynamics, proteins, RNA, or other scientific data.
Excellent programming skills in some prototyping environments such as Python; C++ and parallel programming (e.g., CUDA).
Knowledge of deep learning frameworks, such as PyTorch.
Outstanding research track record.
Excellent communication skills.
We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for computer architecture and technology, we want to hear from you!
Your 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.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, Fundamental Generative AI - 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, Fundamental Generative AI - 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.
