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Head of Quality, AI Business

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Prolific

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Location:
Mexico , Mexico City

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Contract Type:
Not provided

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Salary:

Not provided

Job Description:

As Head of Quality, AI Data, you will own the systems that turn messy human and model signals into trustworthy, scalable AI data. Our customers’ models are only as good as the data and evaluations we deliver—and as we operate across regions, languages, and time zones, quality cannot be an afterthought or a local optimisation. This role sets the global quality bar. You will define standards, enforce rigor, and build quality systems that scale across distributed teams without slowing delivery. You’ll act as the senior quality leader internally and externally, shaping how customers understand, trust, and use Prolific’s data.

Job Responsibility:

  • Set the global quality strategy across annotation, human feedback, model evaluation, red-teaming, and multilingual data
  • Define and enforce quality standards, acceptance criteria, and playbooks across project and pipeline types
  • Own the quality measurement system, including sampling strategies, agreement metrics, defect taxonomies, and drift detection
  • Lead a globally distributed quality organisation and design operating rhythms that work asynchronously across regions
  • Ensure quality is embedded from project kickoff through delivery, including audits, remediation loops, and root-cause analysis
  • Act as the senior quality partner for customers, clearly explaining methodology, results, risks, and improvement plans
  • Partner with Product, Engineering, and Operations to embed quality into tooling, workflows, and automation
  • Hire, develop, and lead quality managers and senior individual contributors, building a culture of rigor and accountability

Requirements:

  • 8–12+ years of experience in quality, data operations, trust and safety, or ML evaluation, with 3+ years leading managers or senior leads
  • Proven experience running quality programs across globally distributed teams and multiple regions
  • Strong statistical intuition (sampling, agreement, bias/variance) and comfort working with quality data
  • Fluency with SQL and dashboards
  • working knowledge of Python or R for analysis or automation
  • Deep understanding of human-in-the-loop systems and how data quality impacts model behaviour
  • Strong judgment balancing speed, cost, and quality, and the ability to make trade-offs explicit
  • Clear, confident communication with both engineers and executives

Nice to have:

  • Experience with multilingual or localisation-style QA
  • Background designing taxonomies or evaluation frameworks tied to model performance
  • Exposure to regulated or high-scrutiny environments where auditability matters
What we offer:
  • competitive salary
  • equity
  • benefits
  • remote working
  • impactful, mission-driven culture
  • opportunity to earn a cash variable element, such as a bonus or commission

Additional Information:

Job Posted:
January 07, 2026

Work Type:
Hybrid work
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