Mercor
Senior Product Manager, Payments
San Francisco · Senior
Sponsorship not specifiedDetected 52 days ago
RailsMachine LearningProduct ManagementPRDsAccountingLeadership
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Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
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About the role
- Getting people paid accurately, quickly, and in the way they expect is the single most important promise we make to our workforce.
- You'll balance long-term platform strategy with rapid execution, making decisions that directly shape expert trust, operational cost, and the company's bottom line.
Responsibilities
- Own the payout experience: Take full ownership of how experts get paid - from contract terms and time capture through disbursement, retries, and support resolution.
- Build the ledger and money movement platform: Partner with engineering on the ledger, reconciliation, and payout automation that keep every dollar correct, traceable, and auditable at scale.
- Understand the business: Work backwards from payout cost, failure rates, support volume, and expert retention to decide what gets built.
- Get in the weeds: Write specs and PRDs, but also build the dashboards, dig through failed payouts, and make small PRs to unblock yourself.
- Collaborate: Partner closely with engineering, finance, compliance, operations, and support to ship quickly without breaking trust.
- Take full ownership of how experts get paid - from contract terms and time capture through disbursement, retries, and support resolution.
- Build the ledger and money movement platform:
Requirements
- Payments depth: Working knowledge of payout rails, ledgers and double-entry accounting, reconciliation, FX, KYC, and tax and compliance requirements across markets.
Nice to have
- 6+ years in product management, with meaningful time on payouts or disbursements specifically - not only payments acceptance or checkout.
- Prior SWE, ML, or DS experience preferred.
- Working knowledge of payout rails, ledgers and double-entry accounting, reconciliation, FX, KYC, and tax and compliance requirements across markets.
- You take full accountability for outcomes, not just outputs - including when money moves incorrectly.
- Able to self-direct in ambiguous contexts, creating clarity for others.
- Technical Fluency:
- User Obsession and Understanding:
- Equally comfortable running rigorous experiments and pushing forward visionary bets.
Compensation
- Bi-annual performance bonus structure
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
- $200 monthly laundry reimbursement
- $200 monthly personal wellness reimbursement
- Health, Dental, Vision insurance
- Expand global coverage: Grow the payout rails, methods, and currencies available to experts, weighing cost, speed, reliability, and local regulation market by market.
Company info
- 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.
This listing is sourced directly from Mercor's careers page and normalized into a canonical job model.