Labeler Operations Lead

Centaur Labs

Centaur Labs

Operations

United States · Remote

Posted on May 27, 2026

Centaur

We Create Superior Data By Making Annotation Competitive

Labeler Operations Lead

$130K - $190KUS / Remote (US)
Job type
Full-time
Role
Operations
Experience
11+ years
Visa
US citizen/visa only
Apply to Centaur and hundreds of other fast-growing YC startups with a single profile.
Apply to role ›

About the role

(Internally we call this Supply Lead)

About Centaur Labs

Centaur Labs is the modern data labeling solution driving AI innovation across the healthcare industry. From agile startups and cutting-edge research labs to global pharmaceutical giants and Big Tech, we empower the entire spectrum of AI. Our expert crowd of 50k+ labelers, combined with our gamified DiagnosUs app for motivation and quality control, ensures scalable, high-quality labels are delivered in as little as 24 hours. We are backed by leading investors including Y Combinator, Matrix, and Accel, and recently closed a Series B led by SignalFire.

About the role

The Supply team keeps a scalable, healthy network of labelers flowing into every Centaur project. As Supply Lead, you own the entire labeler lifecycle - sourcing, contracting, onboarding, paying, supporting, and engaging - across both our app-based labeler community and our network of specialists. Labelers are the single biggest variable in project quality, which makes Supply one of the highest-impact functions in the company. Day-to-day, you make sure every project is staffed with the right people, at the right rate, on time.

This is an AI-native role by design. You'll work alongside systems that surface spend and quality dashboards in real time, track channel performance, and maintain the labeler taxonomy. Your job is to decide where the business goes - labeler payment rates, supply mix, fraud strategy, channel investment - and to push the systems harder where they aren't pulling their weight. The person who thrives here redesigns systems rather than runs them.

The unit economics of how every project gets staffed run through this role. You'll own the rate card, the partner mix, the labeler database, and the labeler experience - and you'll see the impact in our margin within your first quarter.

Responsibilities

  • Own sourcing strategy and cost. Set pricing rate cards, negotiate partner agreements, and define the supply mix across channels.
  • Own contracting. Maintain SOW and contract templates for independent and partner-staffed labelers, plus the security standards we apply to each project. Work directly with outside legal counsel on partner negotiations and contract changes.
  • Own trust and fraud. Run the identity verification, credentialing, and fraud-detection programs that protect both our specialist network and our app-based labeler community. The bad actors evolve with the industry; staying ahead is permanent.
  • Own payments and offboarding. Run the payments cadence across our external payment tools, the offboarding workflow, and the controls that keep payments accurate, on time, and audit-ready.
  • Own labeler experience. Set the frameworks for how labelers are supported on every project - the documentation, the tooling (Intercom), and the KPIs that make sure labelers feel heard and respected. Represent the voice of the labeler to leadership.
  • Own the labeler database and taxonomy. Decide the structure, definitions, and when they change. A well-structured database is what makes independent-labeler-first viable.
  • Manage the Supply team. Lead an agile team, run the cadence (weekly, biweekly metrics review, quarterly planning), and report Supply's KPIs to leadership.

First 90 days

By the end of your first quarter we'd expect real progress on four fronts: an audit of labeler spend with a recommendation on how to bring costs down; a deep dive with Product on how to scale our vetting and credentialing framework; stabilizing the new support workflow; and a plan to prioritize direct sourcing channels so we rely less on staffing partners.

You may be a good fit if you

  • Have 8-10+ years of operational experience, ideally at a labeling, annotation, or crowdsourcing company - or have run a sourcing/staffing network in clinical staffing, an online contractor marketplace, or healthcare contracting
  • Are AI-native. When you see a recurring decision - matching labelers, screening for fraud, pricing a request - your instinct is to design it as a system, not to keep doing it by hand. You have built or contributed to a Claude / Cowork skill, custom GPT, or similar AI workflow inside an ops function
  • Are number-comfortable. Half the job is math - costs, margin, spend tracking, dashboards. You turn messy data into actions weekly
  • Are contract-comfortable. You read an SOW, mark up a partner agreement, and work alongside outside counsel without needing every clause translated
  • Have managed a network of contractors, contingent workers, or crowdsourcing communities before, and understand the general rules of the game
  • Are an operator-entrepreneur. You write the processes, pick the tools, and define the metrics where they don't exist yet
  • Operate under uncertainty. Deadlines aren't yours to set - when Sales closes a deal, the clock starts. Scope shifts mid-flight, and Supply absorbs it
  • Have no ego about your own work. The process you build this quarter may be the one you replace next quarter
  • Are cross-functional. You work closely with Product (the platform our specialists use), Marketing (how we find them), and Sales (how we price them), and you can speak each of their languages
  • Have managed a small team before, including part-time and contract folks, and understand the difference between giving someone a task and giving someone ownership

Strong candidates may also have

  • P&L ownership at a marketplace, staffing platform, or labeling company at scale
  • Experience scaling a labeler or contractor network through 5-10x growth

About Centaur

At Centaur, we create superior-quality data by turning annotation into an arena where experts and AI compete. The best AI models aren’t just trained and evaluated with human data; they’re built with superhuman data. The strongest datasets emerge through collective intelligence, where humans and machines work together to outperform either one alone.