Project Coordinator

$45–55/hrrate as listed

You'd be the operational contact point for AI training-data projects at a major AI lab, translating program leadership's direction into clear guidelines for teams of domain experts. The role is W-2 employment through Cincinnatus LLC, US-based, with observed rates of $45–55/hr.

Summary, eligibility guidance and screening preparation are prepared by Sidequest from the platform's posting. Check the source listing before applying.

What the work actually looks like

This is coordination work on human-data programs, not research and not annotation. Day to day you sit between program leads and a roster of contributing experts: taking direction from leadership, rewriting it as guidelines people can actually follow, answering the questions that come back, and keeping deliverable trackers current in Google Sheets and Excel. You'll onboard new experts as headcount grows, run or take notes in weekly business reviews, and own the action items that come out of them.

A meaningful slice of the job is quality triage. When outputs drift — inconsistent labels, misread instructions, a task type where scores keep dropping — you're expected to notice, dig into root cause, and report findings in a form other teams can act on. That means being comfortable slicing data yourself rather than waiting for an analyst, and being willing to flag a roadblock before it becomes a missed milestone.

What the screen looks for

Verifiable coordination history. Roughly 3+ years running cross-functional projects, with specifics: team sizes, tooling, cadence, what you owned versus what you escalated.
AI-data fluency. Hands-on time on training-data or human-data programs — as coordinator, team lead, EPM, or contributor. Prior EPM or project-lead work on Mercor projects, or comparable programs at Meta, TikTok, or Amazon, is called out as ideal.
Data comfort. Excel depth, working SQL, and enough coding literacy to read what engineers send you. STEM background strongly preferred.
Written clarity. Expect to be probed on how you turn ambiguous leadership input into unambiguous instructions.

Logistics

W-2 employment with Cincinnatus LLC as employer of record, placed within the client AI lab's extended workforce. Must be based in the USA. Expect a real-time meeting cadence — weekly business reviews and ad-hoc calls with program leads — so this is less async than most listings on this board. Observed pay band is $45–55/hr; final rate depends on the placement and is not guaranteed.

What they look for

3+ years project coordination or project management on cross-functional teams
Hands-on experience with AI training-data or human-data programs
Advanced Excel and Google Sheets for deliverable tracking
Working SQL and basic coding literacy
Clear written guideline authoring for distributed expert teams
People management or demonstrated experience leading large groups

Before you apply

Would you pass this screen?

Drawn from what this listing actually requires. Answered in your browser — nothing is sent to us, and we do not store your answers.

Are you currently based in and authorized to work in the United States?
USA-based · required
Do you have at least 3 years of professional experience in project coordination, project management, or equivalent operational leadership role?
3+ years project coordination or management · required
Have you worked on an AI training-data, annotation, human-feedback, or AI-data evaluation project—in a coordinator, lead, EPM, or expert contributor role?
AI data or training-data project experience · required
Do you hold a degree or have formal training/substantial professional background in a STEM field (science, technology, engineering, or mathematics)?
STEM background · preferred
Have you managed, led, or directly supervised a team of three or more people, or demonstrated you can lead and align large groups effectively (e.g., as a team lead or program coordinator on multi-person projects)?
People leadership experience · preferred

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Included with this listing

Interview prep — 11 questions

Matched to what this platform's screening actually measures. Answer each out loud in 60–90 seconds: claim → concrete example → implication.

What it tests: Whether you have hands-on experience translating research or product requirements into actionable work for domain experts, and whether you can articulate the operational structure of an AI training-data or human-annotation program.
A strong answer: Name a concrete project with clear phases or milestones, identify at least two distinct stakeholder groups (e.g., research leads and labelers, or product and data ops), and describe one specific coordination mechanism you used (standups, dashboards, escalation protocol) to maintain visibility and unblock delays.
Where people lose it: Describing a project in generic terms ('I managed timelines and communicated') without naming stakeholders, deliverable types, or a real operational challenge you solved—or conflating coordination with individual execution of project tasks.