White Circle

2 weeks ago

Head of Data Labeling

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 46 minutes agoStatus: Live

Job Summary

Lead the Data Labeling team from scratch—hiring, coaching, and managing performance. Own annotation guidelines, quality standards, QA processes, calibration, and auditing systems. Partner with AI researchers and engineers to convert research objectives into labeling workflows, prioritizing projects by business and research needs. Run complex AI evaluation initiatives across safety and preference ranking (including RLHF and benchmark creation), monitor quality/throughput/cost, and build dashboards to communicate operational insights.

Location: Paris, London

Workplace: Hybrid

Employment Type: Full time

Job Function: Laboratory & Clinical Operations

Seniority: Sr. Director level

Key Responsibilities

•Build from scratch and lead the Data Labeling team, including hiring, coaching, and performance management.
•Define annotation guidelines, quality standards, and evaluation frameworks.
•Develop quality assurance processes, calibration sessions, and auditing systems to maintain consistency.
•Partner with AI researchers and engineers to translate research objectives into labeling workflows and prioritize projects.
•Lead AI evaluation initiatives (safety, preference ranking, RLHF, policy evaluation, benchmark creation) and analyze edge cases to improve guidelines and model performance.

Pay and Benefits

Salary: USD 60,000 - 100,000 annually

Equity and Bonus:Equity

Perks:Paid LeaveRelocation

Key Requirements

•Experience leading data annotation or AI evaluation teams.
•Strong people management and operational skills for scaling processes without losing quality.
•Deep understanding of AI model evaluation, LLM behavior, and modern annotation workflows.
•Experience managing annotation programs for LLMs, generative AI, or machine learning.
•Experience with RLHF, preference data collection, safety evaluations, or benchmark creation.

Experience:AI safetyLLM evaluationData annotationTrust & SafetyContent moderation

Skills:People managementOperational excellenceCommunicationCross-functional collaborationContinuous improvement

Languages:English

Tech Stack:LLMsRLHFPrompt engineeringSQLPythonData analysisBenchmarksDashboardsAnnotation toolingAutomation

Company Brief

White Circle

Builds AI-driven products and services to help businesses automate workflows, extract insights from data, and improve decision-making using machine learning and natural language processing technologies.

Industry: AI & Machine Learning

Website

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White Circle

2 weeks ago

Head of Data Labeling

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 46 minutes agoStatus: Live

Job Summary

Location: Paris, London

Workplace: Hybrid

Employment Type: Full time

Job Function: Laboratory & Clinical Operations

Seniority: Sr. Director level

Key Responsibilities

•Build from scratch and lead the Data Labeling team, including hiring, coaching, and performance management.
•Define annotation guidelines, quality standards, and evaluation frameworks.
•Develop quality assurance processes, calibration sessions, and auditing systems to maintain consistency.
•Partner with AI researchers and engineers to translate research objectives into labeling workflows and prioritize projects.
•Lead AI evaluation initiatives (safety, preference ranking, RLHF, policy evaluation, benchmark creation) and analyze edge cases to improve guidelines and model performance.

Pay and Benefits

Salary: USD 60,000 - 100,000 annually

Equity and Bonus:Equity

Perks:Paid LeaveRelocation

Key Requirements

•Experience leading data annotation or AI evaluation teams.
•Strong people management and operational skills for scaling processes without losing quality.
•Deep understanding of AI model evaluation, LLM behavior, and modern annotation workflows.
•Experience managing annotation programs for LLMs, generative AI, or machine learning.
•Experience with RLHF, preference data collection, safety evaluations, or benchmark creation.

Experience:AI safetyLLM evaluationData annotationTrust & SafetyContent moderation

Skills:People managementOperational excellenceCommunicationCross-functional collaborationContinuous improvement

Languages:English

Tech Stack:LLMsRLHFPrompt engineeringSQLPythonData analysisBenchmarksDashboardsAnnotation toolingAutomation

Company Brief

White Circle

Industry: AI & Machine Learning

Website