Data Annotation Lead

About this role

The AI team owns the models inside the product: resume understanding, candidate-to-role matching, and the assistive tooling recruiters use every day.

Run the labelling that everything upstream depends on: guidelines, a team of annotators, inter-annotator agreement and the honest conversation about where the labels are weak.

These models influence who a recruiter sees, which makes fairness a design constraint rather than a review step at the end. Every ranking change is evaluated for differential impact before it ships, and the team has standing authority to stop a launch. The input is genuinely hard — CVs in every format a human can invent, multilingual and code-mixed text, and documents photographed at an angle in bad light.

Primary responsibilities

• Run the annotation programme that produces the training data everything else depends on
• Write the guidelines, which is most of what decides annotation quality
• Build the quality process: inter-annotator agreement, gold sets, adjudication and feedback
• Manage the annotation team and their throughput and accuracy together
• Handle sensitive data correctly, since annotators are looking at real CVs and real documents

Skills required

Day to day this role works with Annotation, Quality Assurance, Guidelines and Team Management.

• Three or more years running annotation or data quality work
• Have written guidelines that two people applied the same way
• Three or more years leading annotation or data labelling operations
• Writing annotation guidelines, which is most of what decides quality
• Quality processes: inter-annotator agreement, gold sets and adjudication