Product Manager, Generative AI Data

Product Manager, Generative AI Data at NVIDIA

NVIDIA is looking for a Product Manager to support our data strategy for generative AI, focusing on the execution and optimization of synthetic and curated data for large language and visual models. In this role, the responsibilities include day-to-day management of data pipelines that are critical to advancing frontier AI models. Work closely with research and engineering, and help build and deploy the workflows that make GenAI systems safe, effective, and scalable. This is an opportunity to contribute to high-visibility projects and public data releases that define the industry standard!

What You'll Do

• Execute the Data Roadmap: Manage the feature backlog and delivery for synthetic and curated data streams used to train and fine-tune large-scale AI systems.
• Manage Data Workflows: Coordinate the end-to-end lifecycle of data pipelines, including synthetic data generation, human-in-the-loop (HITL) annotation, and reinforcement learning (RL) loops.
• Maintain Quality Frameworks: Implement data quality checks, including coverage analysis, bias detection, and ethical filtering to ensure high-standard model inputs.
• Support Engineering & Research: Act as the bridge between AI researchers and engineers to identify data gaps and deliver the vital datasets or tools to keep development moving.
• Tooling Requirements: Define clear product requirements for internal tools used for data collection, labeling, and augmentation at scale.
• Customer & Partner Coordination: Assist in crafting workflows for enterprise customers or academic partners to enable domain-specific LLM fine-tuning.
• Promote Responsible AI: Ensure data collection and usage align with established legal, privacy, and AI ethics guidelines.

What We're Looking For

• Education: Bachelor’s degree in Computer Science, Data Science, AI/ML, or a related technical field or equivalent experience.
• Experience: 5 + years demonstrated ability in product management, data platforms, or ML-focused roles within a technology company.
• Technical Literacy: Solid understanding of LLM basics (fine-tuning, RAG, and model evaluation) and the machine learning development lifecycle.
• Project Management: Proven track record to manage sophisticated technical projects, hit milestones, and communicate progress to stakeholders.
• Data-Centric Mindset: Familiarity with how data quality impacts model performance, from initial collection to final evaluation.
• Collaboration: Strong communication skills with the ability to translate technical requirements into actionable product tasks.

Ways To Stand Out

• Hands-on experience with Python, SQL, or Spark for data analysis.
• Direct experience with labeling tools (e.g., Labelbox, Scale AI) or synthetic data generation.
• Familiarity with timely engineering or LLM benchmarking.

Key skills/competency

• Generative AI
• Large Language Models
• Data Pipelines
• Product Management
• Machine Learning Lifecycle
• Data Quality
• AI Ethics
• Synthetic Data
• Python/SQL
• Model Evaluation