Nvidia
AI/ML
TechnicalProgramManager,DatasetOperations
Neural analysis suggests this role is
optimal for Senior candidates.
“Technical Program Manager, Dataset Operations at Nvidia. Skills: Technical Program Management, Dataset Operations, AI/ML Data Pipelines, Vendor Management, Data Quality. Lead the end-to-end management of large-scale, multi-modal datasets that power next-generation Physical AI systems. Focus heavily on vendor-sourced data pipelines, ensuring data quality, compliance, scalability, and alignment with research and product goals”
What You'll Achieve.
Ensuring data quality, compliance, scalability, and alignment with research and product goals; Driving execution across complex, high-stakes data programs; Ensuring that we can reliably acquire, manage, and scale the data needed to train next-generation systems
Industry & Context.
What They're Looking For.
Must Have
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, 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, Understanding of Data quality evaluation, Understanding of Dataset biases and coverage challenges, 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
Nice to Have
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)
What You'll Do.
Lead the end-to-end management of large-scale
multi-modal datasets that power next-generation Physical AI systems
Focus heavily on vendor-sourced data pipelines
ensuring data quality
and alignment with research and product goals
Operate at the intersection of research
driving execution across complex
high-stakes data programs
Own the lifecycle of large-scale datasets across modalities
Manage external data vendors end-to-end
Establish scalable processes for multi-vendor coordination
Translate research and model requirements into clear
enforceable data specs
Define and track data quality metrics
Drive continuous improvement via structured feedback loops with vendors
Partner with Research teams
Align dataset strategy with model training and product timelines
Build frameworks for Dataset versioning and traceability
Build frameworks for Vendor performance benchmarking
Build frameworks for Cost vs. quality optimization
Drive automation where possible
but maintain operational rigor
How You'll Work.
Team & Collaboration
Partner with Research teams (to understand evolving model needs); Partner with Engineering teams (data pipelines, storage, tooling); Partner with Legal/compliance (data usage rights, privacy, licensing)
Process & Methodology
program structuring skills (clear specs, milestones, tracking), Ability to convert high-level goals into concrete execution plans, Scope definition, onboarding, contracting, Delivery tracking, quality control, iteration loops
Full Job Description
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
Applying for this Technical Program Manager, Dataset Operations role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Workday
- Workday has a multi-step form — save your progress after every section.
- "Apply With LinkedIn" can fail or lose data; manual entry is more reliable.
- Watch for the "Submit for Review" final step — hitting "Save" alone does not submit.
- Job requisition numbers are useful when following up with HR by email.
ANONYMOUS · UNFILTERED
What do employees actually say about Nvidia?
Real rants from real employees. Read before you apply.