Senior Research Engineer - Enterprise Products
Company websitenvidia.com (NVIDIA, opens in new tab)
Base salary $192,000 to $356,500
Employer-published annual base salary, USD. Advertised base range in Washington +1 more
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationWashington +1 more
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (4 min ago) · observed since
All places named
- Washington
- Santa Clara, CA
About this job
We are now looking for a Senior Research Engineer passionate about Generative AI inference. Are you excited to change the way people infuse AI into products and services? NVIDIA is at the forefront of generative AI models, from language to images. NVIDIA provides building blocks to democratize AI and make generative AI easy to develop, integrate, and deploy. Our team is dedicated to developing optimized inferencing technologies to support our growing generative AI needs. We contribute to all steps of the machine learning lifecycle: from conceptualization, to applied research, engineering for optimized inference, and deployment. Collaborate with research teams, engineers, and open-source community.
What you will be doing:
Design and evaluate routing policies for LLM traffic to best use mixture of model systems.
Build and run agentic benchmarks (e.g., Terminal-Bench ) to measure algorithm quality, and turn results into calibration data and routing profiles
Ship to an open-source repo: design docs, code review, docs, and community contributions
Collaborating with engineering teams across all of NVIDIA to ensure our software integrates seamlessly up and down the NVIDIA accelerated serving stack.
What we need to see:
Bachelor's of Master's degree in Computer Science or equivalent experience.
8+ years of industry experience in Deep Learning frameworks (PyTorch or TensorFlow).
Experience designing or running LLM evaluations/benchmarks — ideally agentic ones — and drawing statistically sound conclusions from them
Understanding of modern techniques in Machine Learning, Deep Neural Networks, Natural Language Processing, or Speech Recognition.
Empirical research mindset: forming hypotheses about new algorithms, running calibrations, iterating on results
Strong communication and interpersonal skills, along with the ability to work in a dynamic and distributed team. A history of mentoring junior engineers and interns is a huge plus.
A desire to constantly grow and learn new things.
Strong computer science fundamentals - algorithms and data structures, computational complexity, parallel and distributed computing, system software.
Ways to stand out from a crowd:
Experience architecting or developing large-scale distributed systems for deep learning.
Agentic benchmark creation and publications.
Knowledge of CPU and/or GPU architecture.
GPU programming (CUDA).
192,000 USD – 304,750 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
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 ($192,000) is above 86% of the 355 Data & ML roles in Washington listed on this site; 5 others list the same floor. Their median floor is $143,700; the middle half runs from $136,000 to $169,050.
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 listingSenior Research Engineer - Enterprise Products$192,000 to $356,500
Manager, Field Application Engineering - OEM Support$192,000 to $304,750
Senior Quantum Applied Research Scientist, Physics Modeling$192,000 to $304,750
Principal Applied Quantum Research Scientist$192,000 to $304,750
Senior Research Scientist, Security and Privacy$192,000 to $356,500
Senior Research Scientist, EDA and AI$192,000 to $356,500
Senior Robotics Research Scientist$192,000 to $356,500
Chart as a table
| Role | Published base |
|---|---|
| Senior Research Engineer - Enterprise Products (this listing) | $192,000 - $356,500 |
| Manager, Field Application Engineering - OEM Support | $192,000 - $304,750 |
| Senior Quantum Applied Research Scientist, Physics Modeling | $192,000 - $304,750 |
| Principal Applied Quantum Research Scientist | $192,000 - $304,750 |
| Senior Research Scientist, Security and Privacy | $192,000 - $356,500 |
| Senior Research Scientist, EDA and AI | $192,000 - $356,500 |
| Senior Robotics Research Scientist | $192,000 - $356,500 |
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, WA, Remote • US, CA, Santa Clara • US, Remote (Levels 4-5 combined)
192,000 USD – 304,750 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
- 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.
