Description
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.
Responsibilities:
- 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
Requirements:
- 8+ 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
Preferred Qualifications:
- 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