Senior Technical Program Manager, Deep Learning Frameworks

Role Overview

Senior Technical Program Manager (TPM) to lead software programs for Deep Learning Training and Inference Frameworks. You will support NVIDIA’s AI researchers and software engineers by driving execution in a highly matrixed environment across software, hardware, and infrastructure.

Responsibilities

• Coordinate delivery of Deep Learning Frameworks programs on existing and new NVIDIA hardware alongside hardware, software, and model program managers, product managers, and engineering teams.
• Drive cross-company alignment on release scope, milestones, risk management, and dependencies (including hardware/software engineering, product, QA, and compliance).
• Manage program execution end-to-end: planning, forecasting, documentation, scheduling, meeting cadence, prioritization, dependencies, reporting, and escalation of critical/blocking issues.
• Define and implement program effectiveness metrics; collect/analyze program data to support planning and data-driven decisions.
• Establish standard processes for open-source contribution and release management within the NVIDIA AI/ML ecosystem.
• Provide program status updates with insights and recommendations to senior management; improve organizational alignment and efficiency by streamlining processes.

Requirements

• Postgraduate degree in CS, AI, Mathematics, or equivalent experience.
• 10+ years of software program management experience with a track record leading global projects across multiple time zones.
• Experience delivering large software programs across multiple layers of the software stack.
• Ability to think strategically and tactically, build consensus, and successfully engage engineering and product teams.
• Strong communication/presentation, attention to detail, and ability to multitask in a fast-changing environment.
• Strong organization skills and experience with tools such as Jira, Aha!, Confluence; and distributed version control such as Git.

Nice to Have

• Experience with deep learning frameworks (e.g., PyTorch, JAX) and ML compilers (e.g., XLA, Triton), plus GPU technology.
• Experience with open-source development and production software delivery.
• Exposure to NVIDIA GPU software stack and tooling (e.g., CUDA Toolkit, cuDNN, TensorRT, NCCL).
• Background in DevOps/process improvement with measurable efficiency gains and engineering experience.