Nvidia Senior Technical Program Manager Generative AI 

United States, California 

647247023

What you'll be doing:

• Drive multi-functional execution across Research Scientists, Research Engineers, Product, Marketing and Legal, acting as the glue to ensure alignment and high velocity.

• Lead generative-AI model building, including model training, post-training, optimization, and release to internal and external users.

• Coordinate and drive open source releases on platforms like GitHub and Hugging Face, ensuring quality, traceability, and findability.

• Collaborate with Legal to ensure all datasets, code, and models are licensed for commercial use and open source distribution.

• Supervise the model lifecycle and its dependencies (e.g., datasets, checkpoints, licenses) and maintain compliance documentation.

• Enable internal NVIDIA teams and early adopters with early access to models and tools; bring together and synthesize feedback to advise roadmap and product iteration.

What we need to see:

• We are looking for an outstanding technical program manager with a consistent record driving sophisticated, cross-functional AI initiatives across research, engineering, and product teams.

• Hands-on experience running generative AI models—whether LLMs, diffusion models, or VLMs/VLAs—along with a working understanding of their inputs, outputs, failure modes, and performance bottlenecks.

• Comfortable working in Python, using tools like Hugging Face, PyTorch, Docker, or similar frameworks to evaluate models, run inference, and understand code-level artifacts (e.g., config files, training checkpoints).

• Familiarity with the full lifecycle of foundation model development: data curation, training, post-training (e.g., distillation, quantization), evaluation, and deployment.

• You will be the connective tissue across science, engineering, legal, and product functions, and translate technical realities into clear program achievements, risk assessments, and execution plans.

• Experience leading open-source or externally-released model artifacts (e.g., GitHub, Hugging Face, licensing, model cards, compliance metadata) is highly valued.

• Strong understanding of AI licensing, model/data provenance, and traceability systems is a major plus.

• Excellent communication and leadership skills are essential—you should be able to influence at all levels, from individual contributors to VPs.

• BS or MS in Computer Science, Engineering, Applied Math, or a related technical field or equivalent experience in an engineering or research role.

• 12+ years of relevant experience, including at least 5 years leading technical programs in ML, AI, or applied research domains.