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.
What You’ll Be Doing:
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.
At NVIDIA, we believe the next generation of AI will be physical AI – systems that perceive, reason, and act in the real world. Building these models requires building robust systems that span across large-scale compute, multimodal datasets, simulation driven synthetic data, and real-time reasoning for robots and autonomous systems. Our Cosmos team sits at the heart of this mission. We build the systems that make it possible to train Cosmos, NVIDIA’s world foundation model for physical AI. Cosmos enables large-scale AI models for robots, autonomous agents, and AI systems to understand, plan, and act in complex environments.
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.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- 5+ years of experience as a TPM, Product Ops, or similar role in AI/ML or data-intensive systems
- 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 computer vision, robotics, or autonomous driving datasets
- Understanding of annotation workflows and data quality evaluation
- Strong program structuring skills and ability to convert high-level goals into execution plans
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”



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