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Product Manager, Real World Data

Mercor

San Francisco, CAFull-time$180–300K/yrPosted todayStill listed today

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At a glance

Compensation
$180–300K/yr
Location
San Francisco, CA
Schedule
Full-time
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

Mercor seeks a Product Manager for Real World Data to shape how real-world data becomes datasets for AI labs. The role spans product strategy and go-to-market, including defining dataset value across training stages, packaging and positioning products, and accelerating delivery. The Product Manager will work with research, environments, sales, and engineering teams to build products informed by customer needs and model performance.

Skills & qualifications

RequiredNice to have

Skills

Product Management, requiredProduct Roadmapping, nice to haveProduct Discovery, nice to haveDataset Specification, nice to haveProduct Packaging, nice to haveQuality Standards, nice to haveScoping, nice to haveSampling, nice to haveQuality Review, nice to haveOwnership, nice to haveSelf-Direction, nice to haveMVP Development, nice to haveStrategic Thinking, nice to haveUser Research, nice to haveCustomer Interviews, nice to haveCommercial Acumen, nice to haveExperimentation, nice to have

Qualifications

3+ Years Product Management, nice to have

Benefits

Relocation Assistance
Medical Insurance
Dental Insurance
Vision Insurance

Full job description

About Mercor

Mercor’s mission is to organize human intelligence for the AI economy. We build the infrastructure that enables frontier AI labs and enterprises to train, evaluate, and improve AI on real-world professional work. More than five million experts have joined our network, and we pay out over $5 million daily for their knowledge and expertise.

We built our training and evaluation infrastructure alongside the world’s leading AI labs. Now, we’re bringing those capabilities to enterprises across industries, enabling them to train, evaluate, and improve AI using their own expertise and standards. Our APEX benchmarks measure how AI performs on economically valuable work, while our enterprise evaluations and post-training capabilities turn those insights into measurable improvements across real-world workflows.

Our work sits at the intersection of frontier AI, human expertise, and real-world application. We’re solving problems few companies have encountered, with the opportunity to influence what the world’s most advanced AI systems become capable of doing. We’re looking for people who bring different perspectives, take ownership, exercise sound judgment, and hold themselves to an exceptionally high standard. You’ll have the opportunity to do consequential work alongside talented colleagues who challenge one another, collaborate openly, and share a commitment to excellence.

Mercor is profitable and recently raised a $750 million Series D at a $20 billion valuation. We work in person five days a week in San Francisco, New York, and London.

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

Mercor is an Equal Opportunity Employer and is committed to providing equal opportunity to all employees and applicants. Mercor does not discriminate based on actual or perceived race, color, creed, religion, national origin, ancestry, citizenship status, age, sex or gender (including pregnancy, childbirth, related medical conditions and lactation), gender identity or gender expression, sexual orientation, marital status, military service and veteran status, disability, protected medical condition as defined by California or local law, genetic information, or any other characteristic protected by applicable federal, California, or local laws and ordinances. Further, Mercor prohibits discrimination, harassment, and retaliation based on any combination of protected characteristics. This Policy applies to all areas of employment, including recruitment, hiring, training, promotion, compensation, benefits, discipline, termination, and all other privileges, terms, and conditions of employment. This Policy and the law prohibit employment discrimination against any employee or applicant based on any legally protected status.

How this job compares

Set against the 7,606 open Product Manager jobs on Olive Jobs, counted November 12, 2026.

Pay
  • This posting$180–300K/yr
  • California median$170–241K/yr1,258 salary ranges
  • US median$140–208K/yr6,067 salary ranges

This range's midpoint, $240K, is 17% above the California median midpoint ($205K) — in the top quarter of Product Manager salary ranges in California.

Openings
Olive Jobs lists 1,487 open Product Manager jobs in California and 7,606 across the US. 10% of them nationwide are listed as remote or flexible.
Hiring the most in California
Experience
Product Manager postings that state a minimum ask for 5 years of experience at the median; the middle half ask for 4 to 7 years (6,526 postings).
Education
2,155 of the 7,606 open Product Manager jobs (28%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 12, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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