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.
Applications for this job will be accepted at least until August 31, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
