Queue Manager / AI Data Quality Lead (Trust & Safety Background) - DP

Queue Manager / Annotation Lead with Trust & Safety Background (AI Data Ops) Start date: Immediate / TBC End Date: TBC Location: Remote Type of contract: Freelance Languages required: English Hourly Rate: Include the rate you are comfortable with on your CV. 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 / AI Data Quality Lead to join a high-priority initiative in partnership with a leading AI company. This is an operational, hands-on role — you will own day-to-day execution for one or more annotation queues on a live AI training/eval program: managing throughput, running quality calibrations, tracking contributor performance, and building out the dashboards/reporting that keep stakeholders informed in real time. We're looking for people who have actually run queues and quality on AI data programs before — not people who've managed generic ops queues and are pivoting into AI. You should be able to speak to specific projects, specific calibration processes you've built, and specific contributor performance systems you've run. For this opening, we specifically want candidates with a trust & safety / integrity background — someone who can tell when responses are shallow, low-effort, or phoned-in, and who keeps queues healthy on quality, not just catches bad actors. Think signal-quality analyst, not a generic queue lead. What "good" looks like for us (based on people we've already hired into similar roles): A quality analyst who has scaled up to running a full AI data program end-to-end — owning calibrations and contributor performance management at program level, not just task level. A queue manager who also operates as an AI training consultant — someone comfortable advising on process/methodology, not just executing it. 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/contributor level Design and run calibration sessions , drive guideline adherence, reduce rework Manage annotator/contributor performance: unassign underperformers, identify and retain high-performers Reporting & Dashboards Build and maintain dashboards to track throughput, disagreement rates, defect/rework rates, and contributor performance Turn raw queue data into clear, actionable reporting for stakeholders Provide feedback for process improvements based on data trends Training & Support Train new annotators/contributors 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 What you'll bring Proven, direct experience running queues and quality on AI data programs — ideally at a competitor (Scale AI, Surge, Appen, Sama, Invisible, Mercor, Alignerr, Handshake AI, iMerit, CloudFactory, Toloka, or similar) 3+ years in high-throughput ops (data labeling, trust & safety, BPO, content ops, CX ops), with recent, specific AI data ops experience Trust & safety / integrity background required Able to identify shallow, low-effort, or phoned-in responses Proven ability to design and run calibration processes from scratch, not just follow existing ones Track record building or maintaining dashboards/reporting (spreadsheets required; SQL/BI/Looker/Tableau a strong plus) Experience managing contributor performance at scale — including retention/removal decisions Comfortable with ambiguity and fast-changing priorities on live programs 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 Consulting-style experience advising clients on AI training methodology, not just executing tasks Success looks like Predictable SLA delivery, a stable backlog, improving quality with declining rework, and dashboards/reporting that give stakeholders real-time visibility without them having to ask. Why Prolific is a great platform to join as an expert participant Joining our platform as a participant will give you the chance to influence the AI models of the future. Once you pass our assessment, you can join Prolific in just 15 minutes and start enjoying competitive pay rates, flexible hours, and the ability to work from home. We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioral data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems. We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviors into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity. 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