Six Figure Work

Relational Foundation Model Engineer, Modern Data Stack

NVIDIA

Company websitenvidia.com (NVIDIA, opens in new tab)

Base salary $184,000  to $356,500

Employer-published annual base salary, USD. Advertised base range in Santa Clara, CA

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  • LocationSanta Clara, CA
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (5 min ago) · observed since

About this job

NVIDIA is redefining what is possible with AI, and the Relational Foundation Model team is helping lead that transformation. We are building a unified foundation model that can understand the structure, context, and relationships within relational databases and heterogeneous graphs—opening a new frontier for enterprise AI. As an engineer on this team, you will go beyond adapting existing models: you will design, build, and evaluate novel Transformer and graph neural network architectures that generalize across diverse data schemas. Your work will power meaningful applications, including recommendation systems, demand forecasting, fraud detection, and predictive maintenance.

You will partner with world-class researchers and engineers across the full machine learning lifecycle, from architecture exploration and large-scale training to post-training optimization and high-performance inference. This is an opportunity to turn foundational research into production systems that influence how organizations derive intelligence from complex, connected data. NVIDIA foundation models are optimized for NVIDIA-accelerated infrastructure, providing a strong platform for translating advanced AI research into deployable systems. If you are energized by graph learning, relational reasoning, and building AI that moves beyond single-table benchmarks, we would love to hear from you


What you’ll be doing:

  • Collaborate with researchers/engineers to enhance our Transformer and GNN-based models to operate seamlessly over any relational schema and heterogeneous graph.

  • Gain hands-on experience with high-impact use cases such as forecasting, entity matching, customer retention and fraud detection – all built on top of a single, extensible foundation model.

  • Leverage your knowledge in ML and AI to tackle real challenges while contributing to scalable and adaptable solutions that push the boundaries of what’s possible.

  • Work may span the full lifecycle of modern ML systems: from architecture design/training to post-training optimization and inference acceleration.

  • You will contribute to our next generation of the Relational Foundation Model. 

What we need to see:

  • MS or PhD in Machine Learning, Computer Science, or equivalent experience

  • Proficiency in Python and deep learning frameworks, such as PyTorch

  • At least 8 years of research experience in designing ML algorithm solutions

  • Practical experience in using Predictive Models in Real World Applications

Ways to stand out from the crowd:

  • Familiarity with graph-based machine learning; publications at venues such as NeurIPS, ICLR, ICML, or similar

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, 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 ranges for this position are:
184,000 USD – 287,500 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)

This range next to 6 other live NVIDIA roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live NVIDIA roles with the nearest advertised base floor
RolePublished base
Relational Foundation Model Engineer, Modern Data Stack (this listing)$184,000 - $356,500
Senior Software Engineer, Subnet Management$184,000 - $356,500
Senior Software Engineer, AI Networking$184,000 - $356,500
Senior Software Engineer, Machine Learning Safety$184,000 - $356,500
Senior Firmware Security Architect, Networking$184,000 - $356,500
Senior Compiler Engineer - AI$184,000 - $287,500
Senior System Software Engineer, Performance - CUDA Driver$184,000 - $356,500

Same $100K to $400K scale as every card. All NVIDIA roles · How to read the bar

Observed changes

  1. First observed on the employer's board
  2. 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 (Levels 4-5 combined)

184,000 USD – 287,500 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.