Principal Technical Program Manager, Relational Deep Learning Platform

Details

NVIDIA is building the next generation of relational deep learning for enterprise data. The platform learns from structures and relationships inside relational databases and heterogeneous graphs, combining GPU-accelerated graph analytics and graph machine learning. It supports workloads such as fraud detection and recommender systems.

The Principal Technical Program Manager will lead the relational deep learning program from research to production, connecting machine learning researchers, infrastructure teams, and platform teams to ensure alignment and delivery of reliable products.

Responsibilities

• Deliver task-specific models for domains such as fraud detection and recommender systems, from problem definition and data requirements through training, benchmarking, and handoff to product and customer teams.
• Coordinate with infrastructure, systems, and platform groups to align compute capacity, training and serving environments, and required platform features.
• Guide release management for the platform and models, including experiment-to-production handoffs, versioning, compatibility, model cards, benchmarks, and safety and compliance approvals.
• Maintain the program operating rhythm, including planning, reviews, risk and dependency tracking, and decision forums across research, engineering, data, product, legal, and other partner teams.
• Define and track program health metrics such as model quality, training speed, evaluation coverage, and time to release.
• Communicate status, risks, and decisions in executive reviews.
• Build, learn, and collaborate across teams to deliver complex programs that create customer impact.

Requirements

• 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 experience 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.
• Ability to work with ML researchers, interpret model and evaluation results, and make decisions involving training pipelines, data, and infrastructure trade-offs.
• Ability to build operating rhythms from scratch, influence without formal authority, and communicate clearly with technical teams and senior executives.
• Familiarity with modern program management practices, including Agile, roadmapping, risk management, and dependency management.
• A hands-on builder mindset, including creating automation and tooling, using AI in daily work, and applying AI to program operations, status reporting, risk detection, and release workflows.

Preferred Experience

• Delivering graph ML, recommender, or fraud-detection systems into production.
• Shipping ML platforms and frameworks used by other teams.
• Experience with graph machine learning, GNNs, relational or tabular data, graph analytics libraries such as cuGraph, and the modern data stack, including warehouses, feature stores, and data pipelines.
• Leading programs spanning platform, infrastructure, model, and research teams, including GPU and compute capacity planning for training and serving.

Benefits

NVIDIA offers medical, dental, and vision insurance; a 401(k) with company match; an employee stock purchase plan; flexible and generous paid time off; parental leave; ongoing learning and development support; equity; and additional benefits.

Applications will be accepted at least until August 31, 2026. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.