Senior Product Manager, Physical AI Robotics Data

NVIDIA•Santa Clara, CA

3d•$168,000 - $327,750•Onsite

About The Position

NVIDIA is seeking a Product Manager to own data strategy for robotics data. Physical Intelligence runs on data. NVIDIA’s robotics data powers the Isaac GR00T and Cosmos models which are advancing the development of Physical AI. NVIDIA Physical AI data roles offer an outstanding opportunity to define the future of deployed physical intelligence. You will collaborate closely with AI researchers, our operations team, and external partners to set an industry standard, build and release datasets, and develop new methodologies for data capture!

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, or similar technical field or equivalent experience.
8+ years of work experience in robotics data, hardware or software development, or product management at a technology company.
Ability to quickly experiment with data to test hypotheses.
Track record of delivering data at scale for AI applications.
Strong communication skills and evidence of ability to influence others.
Prior success delivering ambitious projects for frontier AI.

Nice To Haves

Experience with Physical AI data, including teleoperation data collection, curation, annotation, or quality control.
Development of data collection or annotation workflows, process and guidelines.
A background in ML research or robotics.
Previous experience owning a product portfolio and delivering results.

Responsibilities

Be the key point person for all things robotics training data: requirements gathering, data collection, quality assurance, partner discussion, and data impact evaluation.
Craft and implement robust data frameworks and standards for robotics data: data formats, quality requirements, and data distribution.
Provide strategic direction to internal operations on data collection and annotation, ensuring data supports the goals of the research and engineering teams.
Collaborate with internal and external deep learning engineers and researchers to build short and long term data acquisition plans.
Forge strategic partnerships and collaborations to acquire high-quality, diverse data sources essential for the development and fine-tuning of robotics foundation models.
Contribute to the creation and refinement of tools and technologies for efficient data collection and curation.