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Data Quality Engineer, AI Business

Prolific - North America

Posted Jun 7, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
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Childcare support
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Learning budget
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Verification
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Salary
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Market context

U.S. role benchmark (BLS OEWS)
$116,543 U.S. median for this role
Projected growth (BLS Employment Projections)
+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function
Engineering From the posting source checked Jun 20, 2026
Seniority
Mid From the posting source checked Jun 20, 2026

Schedule

Shift type
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Weekend work
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Company

Equity
Offered From the posting source checked Jun 20, 2026

Application

Cover letter
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Assessment
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Deadline
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Where they hire

State eligibility is not yet verified.

About this role

Data Quality Engineer, AI Business North America Data Quality Engineer, AI Business Team: Client Services Prolific Prolific isn't just enabling AI innovation - we're redefining it. While foundational AI technologies are becoming commoditized, Prolific's human data infrastructure provides the high-quality, diverse data required to train the next generation of AI models. Through our platform, we empower researchers and companies to access a global, ethically curated participant base, ensuring cutting-edge AI research and training grounded in inclusivity and precision. The Role As a Data Quality Engineer within Prolific AI Data Services, you will be the quality guardian for our managed service studies. You will design and operationalise the measurement systems, automation, and launch gates that ensure the data we deliver is trustworthy, authentic, and scalable. This role sits at the intersection of data quality, automation, and integrity. You'll work closely with Product, Engineering, Operations, and Client teams to embed quality and authenticity into study design and execution-enabling faster launches without compromising trust as task types and volumes evolve. What You'll Be Doing Own end-to-end quality design for Prolific managed service studies, including rubrics, acceptance criteria, defect taxonomies, severity models, and clear definitions of done. Define, implement, and maintain quality measurement systems, including sampling plans, golden sets, calibration protocols, agreement targets, adjudication workflows, and drift detection. Build and deploy automated quality checks and launch gates using Python and SQL, such as schema and format validation, completeness checks, anomaly detection, consistency testing, and label distribution monitoring. Design and run launch readiness processes, including

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