Senior Technical Program Manager, Deep Learning Frameworks

Role Overview

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

Responsibilities

• Deliver deep learning frameworks programs on existing and new hardware in partnership with hardware, software, model program managers, product managers, and engineering teams.
• Coordinate cross-company teams (hardware/software engineering, product, QA, compliance) to align on release scope, milestones, risk management, and dependencies.
• Own end-to-end program management: planning, forecasting, documentation, scheduling, meeting effectiveness, prioritization, dependency management, and handling critical/blocking issues.
• Create and run program effectiveness metrics, collecting/analyzing data to support planning and data-driven decisions.
• Define and standardize processes for open-source contribution and release management within NVIDIA’s AI/ML ecosystem.
• Report program status to senior management with insights and recommendations.
• Drive organizational alignment and efficiency by streamlining processes with multi-functional leads.

Requirements

• Postgraduate degree in Computer Science, Artificial Intelligence, Mathematics, or equivalent experience.
• 10+ years of software program management experience, including leading global projects across multiple time zones.
• Proven ability delivering large software programs across multiple layers of the stack.
• Strategic and tactical mindset with strong communication and consensus-building across engineering and product teams.
• Excellent technical presentation, attention to detail, and ability to multitask in a shifting-priority environment.
• Strong organization and tooling experience with Jira, Aha!, Confluence, and Git.

Nice to Haves

• Experience with Deep Learning Frameworks (e.g., PyTorch, JAX).
• Experience with ML compilers (e.g., XLA, Triton) and GPU technology.
• Open-source development experience.
• Production software development and release management experience.
• DevOps/process improvement background with measurable efficiency gains.
• Exposure to NVIDIA GPU software stack (e.g., CUDA Toolkit, cuDNN, TensorRT, NCCL).
• Engineering background.