Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 4
Agentic AI @ 4
Communication @ 4
Compliance @ 7
Data Pipelines @ 4
GenAI @ 6
LLM @ 7
Machine Learning
Prioritization @ 9
Reporting @ 4
Robotics
Security
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
The Nemotron Edge PMO organization seeks a Technical Program Manager to oversee the collection, curation, and release of massive-scale datasets. The role will build the data foundation that enables NVIDIA's models to lead in enterprise and agentic AI, delivering language understanding and synthetic data generation optimized for NVIDIA infrastructure.
Responsibilities
- Drive execution for sourcing, curating, and maintaining high-quality data used to train and evaluate Robotics and LLM programs.
- Identify, evaluate, and onboard external data and 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.
- Create dashboards and reports 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.
Requirements
- 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.
- A consistent track record of leading and successfully delivering medium-to-large, organization-wide programs and projects.
- Experience with AI/ML data vendors, including annotation, evaluation, and labeling platforms.
- Comfort working with research teams that have rapidly changing requirements.
- An AI-native mindset and experience using tooling to automate vendor reporting, tracking, and communication.
- Ability to operate in ambiguity and adapt to rapid pivots in fast-changing GenAI vendor environments.
Preferred Qualifications
- Strong understanding of data governance, data quality, and compliance frameworks.
- Proven 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.
- A track record of driving measurable cost savings or quality improvements through vendor relationship management.
- Experience building vendor scorecards, playbooks, or tracking tools that were adopted by teams.
Compensation and Benefits
- Base salary range: $168,000-$258,750 for Level 4, or $200,000-$322,000 for Level 5.
- Eligible for equity and benefits.
- Applications will be accepted at least until October 17, 2026.
- NVIDIA is an equal opportunity employer and is committed to fostering an inclusive work environment.
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