NVIDIA is redefining what is possible with AI, and we are building the next generation of relational deep learning for enterprise data. Our platform learns directly from the structure and relationships inside relational databases and heterogeneous graphs, unifying GPU‑accelerated graph analytics and graph machine learning in a single stack. It powers high‑impact workloads such as fraud detection and recommender systems and helps customers unlock more value from their data. We care deeply about turning frontier AI research into reliable products that teams can trust every day, and we are excited to add a Principal Technical Program Manager who will help us do exactly that!
What you will be doing:
As Principal Technical Program Manager, you will lead the relational deep learning program from research to production. You will connect ML researchers, infrastructure, and platform teams so work stays aligned and delivers real impact.
Deliver task‑specific models for domains such as fraud detection and recommender systems, moving from problem definition and data requirements through training, benchmarking, and hand‑off to product and customer teams.
Coordinate closely with infrastructure, systems, and platform groups to align compute capacity, training and serving environments, and platform features that models depend on.
Guide release management for both the platform and models, including experiment‑to‑production hand‑offs, versioning, compatibility, model cards, benchmarks, and safety and compliance approvals.
Maintain the operating rhythm for the program, leading planning, reviews, risk and dependency tracking, and decision forums across research, engineering, data, product, legal, and other partners.
Define and track program health metrics such as model quality, training speed, evaluation coverage, and time‑to‑release, and share clear status, risks, and decisions in executive reviews.
We work as one team, we solve hard problems together, and we celebrate when complex programs ship and make a difference for customers.
We believe people who enjoy building, learning, and collaborating across teams will thrive in this role.
What we need to see:
Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent experience.
15+ years of experience in technical program management, engineering, or data/ML delivery, including significant time in ML/AI or large‑scale data environments.
Experience leading complex, multi‑stakeholder programs end to end in research and engineering organizations, with evolving requirements and clear delivery timelines.
Comfort working with ML researchers, interpreting model and evaluation results, and making decisions about training pipelines, data, and infrastructure trade‑offs.
Ability to build operating rhythms from scratch, influence without formal authority, and communicate clearly with both highly technical teams and senior executives.
Familiarity with modern program‑management practices (for example, Agile, roadmapping, risk and dependency management) and the judgment to use them effectively in fast‑moving research settings.
A hands‑on, builder mindset that includes creating automation and tooling, using AI in daily work, and applying AI to streamline program operations, status reporting, risk detection, and release workflows.
Ways to stand out from the crowd:
Delivering graph ML, recommender, or fraud‑detection systems into production, or shipping ML platforms and frameworks that other teams build on.
Working with graph machine learning, GNNs, relational or tabular data, graph analytics libraries such as cuGraph, and the modern data stack (warehouses, feature stores, and data pipelines).
Running programs that span platform and infrastructure teams and model and research teams, including GPU and compute capacity planning for training and serving.
NVIDIA offers comprehensive benefits: medical, dental, and vision insurance; a 401(k) with company match; an employee stock purchase plan; flexible, generous paid time off; parental leave; and ongoing learning and development support!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 240,000 USD - 379,500 USD.You will also be eligible for equity and benefits.
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.Skills Required
- Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent experience.
- 15+ years of experience in technical program management, engineering, or data/ML delivery.
- Significant experience working in ML/AI or large-scale data environments.
- Experience leading complex, multi-stakeholder programs end to end in research and engineering organizations.
- Ability to work with evolving requirements and establish clear delivery timelines.
- Experience interpreting ML model and evaluation results and making training pipeline, data, and infrastructure trade-offs.
- Ability to build operating rhythms from scratch and influence without formal authority.
- Clear communication skills with highly technical teams and senior executives.
- Familiarity with Agile, roadmapping, risk management, and dependency management.
- Hands-on builder mindset, including creating automation and tooling and using AI to streamline program operations and release workflows.
- Experience delivering graph ML, recommender, or fraud-detection systems into production.
- Experience shipping ML platforms or frameworks used by other teams.
- Experience with graph machine learning, GNNs, relational or tabular data, cuGraph, warehouses, feature stores, and data pipelines.
- Experience running programs spanning platform, infrastructure, model, and research teams, including GPU and compute capacity planning.
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
