🎁 Before you apply, rehearse this interview. Create your free WorkMundi account and get an Interview Training on HelpsYouSpeak — no cost, no card. I want my training →
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 the pay of employees in similar positions. The base salary range is 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 August 21, 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.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.