Product Manager, Real World Data

About Mercor

Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.
 
Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.

About the Team

Frontier models have been trained on most of the public web. The next gains will come from how work actually gets done inside companies: the documents, spreadsheets, code, email, chat, and business systems where real decisions get made, each with its own structure and quirks. That data is private, messy, and inconsistent, and turning it into training data that labs can use and trust is an unsolved problem. The Data Acquisition team works on that problem, turning real-world data into datasets that frontier labs use to train and evaluate their models. Our work spans domains from healthcare and engineering to finance and legal. The same data is valuable at every stage of training, from pre-training to the environments where agents learn to do real work.

About the Role

As a Product Manager for Real World Data, you will own how real-world data becomes datasets labs want to buy. You will define what makes this data useful at each stage of training, decide how datasets are shaped, packaged, and delivered, and get high-quality data into labs' hands faster. The role spans product and go-to-market: you will need to understand what is in the data, what labs need, and how to sell it. Working this close to real work, you will see firsthand where frontier models fall short on the tasks that matter most. Real-world data is a new category of product, and what you build will help define it and shape what the next generation of models learns from.

In this role, you will:

- Build New Product Lines: Partner with research and environments teams to make real-world data useful for post-training, so agents learn the messy, judgment-heavy work they will face in real workplaces.
- Own the Roadmap: Define success in terms of sellable datasets, and use lab feedback, sales outcomes, and unmet demand to decide what the team builds next.
- Lead Product Discovery: Define what makes real-world data valuable for pre-training, mid-training, and post-training, and turn that understanding into dataset specifications, quality standards, and ways to measure impact on models.
- Define Packaging and Positioning: Turn acquired data into off-the-shelf dataset products, deciding what is sellable, to whom, and in what form.
- Set the Quality Bar: Set standards for how datasets are structured, documented, and delivered, and build the visibility to catch problems before delivery and trace each one to its source.
- Improve Time to Value: Shorten the path from customer request to accepted delivery by tightening scoping, sampling, and quality review.

You might thrive in this role if you:

- Experience: Have 3+ years as a product manager, prior experience in SWE, ML, or DS preferred.
- High Ownership: Take full accountability for outcomes, not just outputs.
- Independence: Are able to self-direct in ambiguous contexts, creating clarity for others.
- Technical Fluency: Are comfortable building scrappy MVPs yourself when needed to validate direction, unblock engineering, or accelerate iteration.
- Strategic Vision: Have a strong ability to connect user needs and business context to long-term product direction.
- User Obsession and Understanding: Talk to users frequently, know how to effectively conduct user research and customer interviews.
- Commercial Instincts: Enjoy the commercial side of product work, and are as effective with lab researchers and account teams as with engineers.
- Balance of Metrics & Vision: Are equally comfortable running rigorous experiments and pushing forward visionary bets.

Benefits

- Bi-annual performance bonus structure
- Generous equity grant vested over 4 years
- Up to $15k Relocation bonus
- $10K housing bonus (if you live within 0.5 miles of our office)
- $1.5K monthly stipend for meals
- Free Equinox membership
- $200 monthly laundry reimbursement
- $200 monthly personal wellness reimbursement
- Health, Dental, Vision insurance

Compensation

$180K – $300K • Offers Equity