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Queue Manager / Annotation Lead with Trust & Safety Background (AI Data Ops)

United StatesUnited States
Freelance
Not Disclosed
Mid-Level

Job Description

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About Prolific

Prolific is not just another player in the AI space. We are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills.

The Role

We are seeking a Queue Manager / Annotation Lead to join a high-priority initiative in partnership with a leading AI company. You will own day-to-day execution for one or more annotation queues, keeping work flowing, quality on target, and stakeholders unblocked - balancing throughput, SLAs, and accuracy in a live human-data pipeline.

In short, the role involves owning day-to-day execution of one or more annotation queues - managing intake, prioritization, and SLAs, running QA and calibration to keep quality on target, training and supporting annotators, and tracking key metrics like throughput and rework rates.

For this particular opening, we're specifically looking for candidates with a trust & safety / integrity background - someone who can tell when responses are shallow, low-effort, or phoned-in, and who can keep queues healthy on quality, not just catch bad actors. Think signal-quality analyst rather than a general queue lead.

What you'll be doing

Queue Operations & Task Management

  • Manage work queue: intake, triage, prioritization, task assignment, and SLA delivery
  • Monitor task queue and backlog control
  • Identify and troubleshoot bottlenecks (unclear policy, tooling issues, supply gaps)

Quality Assurance & Performance Management

  • Perform QA: make corrections, provide annotator feedback, flag systematic confusion to Client Delivery Lead
  • Monitor quality at project and individual annotator levels
  • Drive guideline adherence, run calibration sessions, reduce rework
  • Manage annotator performance: unassign underperformers, identify high-performers

Training & Support

  • Train new annotators on project guidelines
  • Conduct live or recorded webinars as participants join a project
  • Host "office hours” for participants
  • Oversee dedicated Slack channels: answer questions, provide support, escalate complex issues to Client Delivery Lead

Metrics & Continuous Improvement

  • Track key metrics: throughput, disagreement rates, defect/rework rates
  • Provide feedback for process improvements

What you'll bring

  • 3+ years in high-throughput ops (data labeling, trust & safety, BPO, content ops, CX ops, or similar)

Trust & safety / integrity background required

  • Able to identify shallow, low-effort, or phoned-in responses.
  • Proven queue management under ambiguity (prioritization + execution)
  • Strong quality instincts; can spot systematic errors and close the loop with training/QA
  • Comfortable with metrics and tooling (spreadsheets required; SQL/BI a plus)

Bonus

  • Experience with ML data / LLM eval workflows (ranking, rubric-based judging, gold sets, calibration)
  • Distributed team coordination across time zones; vendor/contract workforce experience

Success looks like

Predictable SLA delivery, a stable backlog, and improving quality with declining rework.

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