2 months ago
Head of AI Data Labeling (AI)
60 000 - 100 000$
Match & Cover letter
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Job description
Text:
TL;DR
Head of AI Data Labeling (AI): Building and leading the data annotation team to support AI safety and model training with an accent on evaluation frameworks, quality assurance, and RLHF workflows. Focus on scaling annotation operations, managing distributed teams, and translating research objectives into high-quality training data for LLMs.
Location: Must be based in Paris (relocation available) or London (no relocation support)
Salary: $60,000 – $100,000 + Equity
Company
is an AI safety startup building a reliability and optimization layer for AI systems through natural-language policy enforcement.
What you will do
- Build and lead the Data Labeling team, including hiring and performance management.
- Define annotation guidelines, quality standards, and evaluation frameworks.
- Partner with AI researchers to translate research objectives into labeling workflows.
- Monitor operational metrics such as quality, consistency, and throughput.
- Lead complex AI evaluation projects including safety, preference ranking, and RLHF.
- Manage vendor relationships and ensure consistent quality across distributed teams.
Requirements
- Must be based in or able to relocate to Paris, or based in London.
- Experience leading data annotation or AI evaluation teams.
- Strong operational and people management skills.
- Deep understanding of LLM behavior and modern annotation workflows.
- Ability to design scalable processes without sacrificing quality.
- Experience managing distributed or global annotation teams.
Nice to have
- Experience with RLHF, preference data collection, or benchmark creation.
- Background in Trust & Safety, AI Safety, or ML Ops.
- Proficiency in SQL or Python for data analysis.
- Experience building internal annotation platforms or workflow automation.
Culture & Benefits
- Competitive salary and equity package.
- Hardware, tools, and subscriptions for AI agents and IDEs provided.
- Paid time off in line with local regulations.
- Two team off-sites per year (e.g., Alps, Saint-Tropez).
- Fast-moving startup environment with high impact.
Hiring process
- Intro call with HR (30 min).
- Take-home exercise.
- Final conversation with the CEO (45 min).
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