Principal Technical Program Manager, Relational Deep Learning Platform

• 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.
• 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.
• 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.
• 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.

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