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Technical Program Manager, Dataset Operations

External
NVIDIA logoNvidia · Santa Clara, CA
Full-timeOn-site1mo ago30+ days old, may be filled
ExpressComputer Vision
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Responsibilities

  • Dataset & Vendor Program Management
  • Own the lifecycle of large-scale datasets across modalities:
  • Ego-centric video (AR/VR, human interaction)
  • Robotics data (manipulation, embodied AI)
  • Autonomous driving data (multi-sensor, multi-agent)
  • Manage external data vendors end-to-end:
  • Scope definition, onboarding, and contracting
  • Data specification and annotation guidelines
  • Delivery tracking, quality control, and iteration loops
  • Establish scalable processes for multi-vendor coordination
  • Data Quality & Specification
  • Translate research and model requirements into clear, enforceable data specs
  • Define and track data quality metrics (coverage, diversity, labeling accuracy, temporal consistency)
  • Drive continuous improvement via structured feedback loops with vendors
  • Cross-Functional Execution
  • Partner with:
  • Research teams (to understand evolving model needs)
  • Engineering teams (data pipelines, storage, tooling)
  • Legal/compliance (data usage rights, privacy, licensing)
  • Align dataset strategy with model training and product timelines
  • Scaling Data Systems
  • Build frameworks for:
  • Dataset versioning and traceability
  • Vendor performance benchmarking
  • Cost vs. quality optimization
  • Drive automation where possible, but maintain strong operational rigor
  • What we need to see:
  • 5+ years of experience as a TPM, Product Ops, or similar role in AI/ML or data-intensive systems and Masters degree (or equivalent experience)
  • Proven experience managing external vendors or large-scale data programs
  • Strong understanding of ML data pipelines and dataset lifecycle
  • Ability to operate in ambiguous, fast-moving research environments
  • Familiarity with one or more:
  • Computer vision / video datasets
  • Robotics / embodied AI data
  • Autonomous driving datasets
  • Understanding of:
  • Annotation workflows
  • Data quality evaluation
  • Dataset biases and coverage challenges
  • Strong program structuring skills (clear specs, milestones, tracking)
  • Ability to convert high-level goals into concrete execution plans
  • Comfortable working across research, engineering, and external partner
  • Ways to stand out from the crowd:
  • Experience with multi-modal datasets (video, sensor, action data)
  • Background in robotics, self-driving, or AR/VR
  • Experience building vendor ecosystems from scratch
  • Familiarity with data compliance (GDPR, privacy, licensing constraints)
  • Why This Role Matters:
  • High-quality data is the foundation of Physical AI. As models evolve toward world understanding and action, dataset complexity increases dramatically. This role is critical to ensuring that we can reliably acquire, manage, and scale the data needed to train next-generation systems.
  • Please join us and be part of the forefront of developing physical AI, general-purpose robots and large-scale foundation models!
  • Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 258,750 USD for Level 4, and 200,000 USD - 322,000 USD for Level 5. You will also be eligible for equity and benefits .
  • Applications for this job will be accepted at least until May 21, 2026. This posting is for an existing vacancy.
  • NVIDIA uses AI tools in its recruiting processes.

Additional Information

We are looking for a Technical Program Manager (TPM) to lead the end-to-end management of large-scale, multi-modal datasets that power next-generation Physical AI systems. This role will focus heavily on vendor-sourced data pipelines, ensuring data quality, compliance, scalability, and alignment with research and product goals. You will operate at the intersection of research, engineering, data vendors, and legal/compliance, driving execution across complex, high-stakes data programs.


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