The Nemotron Edge PMO organization seeks a Technical Program Manager to oversee the collection, curation, and release of massive-scale datasets. In this position, the TPgM will build the data foundation that enables NVIDIA’s models to lead in enterprise and agentic AI, delivering premier language understanding and synthetic data generation optimized for NVIDIA infrastructure.
What you will be doing:
- Drive execution for sourcing, curating, and maintaining high‑quality data used to train and evaluate Robotics/LLM programs
- Identify, evaluate, and onboard external data/annotation vendors aligned with LLM use cases, quality needs, and compliance constraints.
- Negotiate contracts, pricing, SLAs, and KPIs with vendors; track performance and drive continuous improvement and cost efficiency.
- Partner with Legal, Privacy, and Security to ensure data contracts, access, and usage comply with regulatory and internal policies.
- Dashboards and reporting to monitor data quality, vendor throughput, turnaround time, and budget utilization.
- Create and maintain documentation, playbooks, and processes for repeatable, scalable LLM data and vendor operations.
What we need to see:
- 6+ years of experience in data operations, vendor management, or technical program management—preferably supporting AI/ML or LLM initiatives.
- Bachelors degree or equivalent experience
- Exceptional skills in prioritizing and building alignment.
- Consistent track record of leading and successfully delivering medium to large organizational-wide programs and projects.
- Experience with AI/ML data vendors (annotation, eval, labeling platforms)
- Comfort working with research teams who have fast-changing requirements
- AI-native mindset — uses tooling to automate vendor reporting, tracking, and communication
- Ability to operate in ambiguity and rapid pivots — vendor scopes change fast in GenAI.
Ways to stand out from the crowd:
- Strong understanding of data governance, data quality, and compliance frameworks.
- Proven experience managing external data vendors, setting KPIs, SLAs, and performance metrics.
- Working knowledge of LLM training data pipelines, annotation workflows, and synthetic data generation.
- Proven track record of driving measurable cost savings or quality improvements directly tied to how you structured and managed vendor relationships
- Built vendor scorecards, playbooks, or tracking tools that were adopted as well as being comfortable working with research teams in fast-moving GenAI environments where vendor scope changes frequently and pivots are the norm
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking and versatile people in the world working with us, and our engineering teams are growing fast in some of the most impactful fields of our generation: AI, Data Engineering, and Data Science. If you're a creative engineer who enjoys autonomy and shares our passion for technology, we want to hear from you.
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 an inclusive 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
- 6+ years of experience in data operations, vendor management, or technical program management, preferably supporting AI/ML or LLM initiatives
- Bachelor’s degree or equivalent experience
- Exceptional prioritization and alignment-building skills
- Track record of leading and delivering medium- to large-scale organizational programs and projects
- Experience with AI/ML data vendors, including annotation, evaluation, or labeling platforms
- Ability to work with research teams whose requirements change rapidly
- Experience using tooling to automate vendor reporting, tracking, and communication
- Ability to operate effectively amid ambiguity and rapid changes in generative AI vendor scopes
- Understanding of data governance, data quality, and compliance frameworks
- Experience managing external data vendors and setting KPIs, SLAs, and performance metrics
- Working knowledge of LLM training data pipelines, annotation workflows, and synthetic data generation
- Track record of achieving measurable cost savings or quality improvements through vendor management
- Experience building vendor scorecards, playbooks, or tracking tools adopted by organizations
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.”
