Data Product Manager, Generative AI

Posted 14 Days Ago
Be an Early Applicant
Santa Clara, CA, USA
In-Office
168K-328K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Lead generative-data strategy and roadmaps for LLMs and visual models. Build end-to-end data pipelines (synthetic generation, HITL, RL loops), define data quality and evaluation frameworks, partner with researchers, engineers, customers, and legal/ethics to enable safe, scalable model training, fine-tuning, and deployment, and establish external partnerships for dataset access.
Summary Generated by Built In

NVIDIA needs a Senior Product Manager to drive NVIDIA's data strategy for generative AI, with a focus on synthetic and curated data for large language and visual models. In this role, you will craft the future of how data is built, refined, and deployed to advance frontier AI models. Working at the intersection of product, research, and engineering, you will craft and lead end-to-end data pipelines that are critical to safe, effective, and scalable GenAI systems. NVIDIA is committed to public data release, where your work will be prominently featured. This is a high-impact position that requires a rare mix of deep technical understanding, product intuition, and cross-functional leadership.

What you’ll be doing:

  • Lead the generative data roadmap—define and evolve our strategy for synthetic, curated, and real-world data used to train, fine-tune, and evaluate large-scale AI systems for a specific modality or model type.

  • Craft and lead data pipelines that power model customization, alignment, and evaluation—including synthetic data generation, human-in-the-loop (HITL) workflows, and RL loops.

  • Establish thorough data quality frameworks, including coverage analysis, bias detection, adversarial testing, and ethical filtering.

  • Partner with AI researchers and engineers to identify data bottlenecks in model development, then deliver data, tools or workflows to unblock them.

  • Define product requirements for internal tools supporting data collection, annotation, and augmentation at scale.

  • Collaborate with enterprise customers to design workflows for domain-specific LLM fine-tuning using synthetic or proprietary datasets.

  • Drive initiatives on responsible data use, including fairness, visibility, and privacy, in close alignment with legal, compliance, and AI ethics teams.

  • Lead cross-functional efforts with infrastructure, model training, and deployment teams to ensure that data is usable, scalable, and aligned with research goals.

  • Forge strategic partnerships with academic labs, data vendors, and open-source communities to expand access to high-quality and diverse datasets.

What We need to see:

  • Bachelor’s or Master’s in Computer Science, Data Science, AI/ML, or a related technical field (or equivalent experience).

  • 8+ years of experience

  • Demonstrated ability in product management, data platform leadership, or ML/AI-focused roles at a technology company

  • Strong understanding of LLM architecture, training regimes, and alignment methods (e.g. fine-tuning, RL, retrieval-augmented generation)

  • Consistent track record in running large-scale data projects or pipelines for machine learning applications

  • Deep familiarity with data-centric AI development, from collection to evaluation

  • Outstanding communication skills—ability to translate between research, engineering, and business collaborators

  • Proven ability to prioritize optimally and ship sophisticated cross-functional projects

Ways to stand out from the crowd:

  • Experience with GenAI data workflows: prompt engineering, synthetic data generation, human feedback systems

  • Prior work on LLM evaluation frameworks or benchmarks

  • Experience developing data quality, labeling, or annotation tools

  • Knowledge of data governance, privacy, or AI ethics standard processes

  • Exposure to enterprise ML use cases and multi-modal model development

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most hard-working and dedicated people on the planet working for us and, due to unprecedented growth, our product management teams are growing fast. If you're a creative with a genuine 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 208,000 USD - 327,750 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 10, 2026.

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

  • Bachelor's or Master's in Computer Science, Data Science, AI/ML, or related technical field (or equivalent experience).
  • 8+ years of experience.
  • Product management, data platform leadership, or ML/AI-focused role experience at a technology company.
  • Strong understanding of LLM architecture, training regimes, and alignment methods (fine-tuning, RL, RAG).
  • Proven track record running large-scale data projects or pipelines for machine learning applications.
  • Deep familiarity with data-centric AI development from collection through evaluation.
  • Outstanding communication skills and ability to translate between research, engineering, and business stakeholders.
  • Proven ability to prioritize and ship sophisticated cross-functional projects.
  • Experience with GenAI data workflows (prompt engineering, synthetic data generation, human feedback systems).
  • Prior work on LLM evaluation frameworks or benchmarks.
  • Experience developing data quality, labeling, or annotation tools.
  • Knowledge of data governance, privacy, or AI ethics processes.
  • Exposure to enterprise ML use cases and multi-modal model development.

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.

  • 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.
  • 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.
  • 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

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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.”

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