Senior Data Labeler

White Circle; Paris; Hybride; EUR 90 000 - 130 000; Plein temps

Avantages offerts par ce poste

Equity compensation

Hybrid work Paris

Relocation package

Health insurance France

Learning & development

Team off-sites

Résumé du poste

White Circle is seeking a Data Labeling Lead to build and guide the annotation team in safety evals, RLHF, and benchmarks. You will own quality, throughput, and cost while partnering with AI researchers.

Lead from scratch with hiring, guidelines, and evaluation frameworks; drive scalable labeling workflows and robust QA processes in a fast-moving startup environment.

Qualifications

• Has experience leading data annotation or AI evaluation teams.
• Understands AI model evaluation, LLM behavior, and modern annotation workflows.
• Can design scalable processes without sacrificing quality.
• Communicates clearly across technical and non-technical teams.

Responsabilités

• Build from scratch and lead the Data Labeling team (hiring, coaching, and performance management).
• Define annotation guidelines, quality standards, and evaluation frameworks.
• Develop quality assurance processes, calibration sessions, and auditing systems.
• Partner with AI researchers and engineers to translate research objectives into labeling workflows.
• Prioritize labeling projects based on business and research needs.
• Monitor operational metrics including quality, consistency, throughput, and cost.
• Improve annotation tooling, automation, and workflow efficiency.
• Lead complex AI evaluation projects, including safety, preference ranking, RLHF, policy evaluation, and benchmark creation.
• Analyze disagreement patterns and edge cases to improve guidelines and model performance.
• Manage vendor relationships and ensure consistent quality across distributed teams.
• Build reporting dashboards and communicate operational insights to leadership.
• Foster a culture of continuous improvement, accountability, and operational excellence.

Connaissances

Data labeling leadership

People management

Quality assurance

Process design

Cross-functional collaboration

Outils

SQL

Python

Description du poste

ABOUT US

TL;DR: We\'re looking for a Data Labeling Lead to build our annotation team from zero - setting quality standards, designing evaluation frameworks, and running the labeling operations behind our safety evals, RLHF, and benchmarks. You\'ll own quality, throughput, and cost while working side by side with our AI researchers.

White Circle https://whitecircle.ai/ is an AI Safety company building the safety, reliability, and optimization layer for AI systems. At the core of our platform are policies - simple natural-language rules that define what an AI model should and shouldn\'t do. We automatically test, enforce, and continuously improve these policies at scale.

• We\'ve raised $11M from top funds, founders, and senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and others
• We process over 100M+ API calls every month
• We fine-tune and train our own LLMs so they run faster and cheaper than any open or proprietary model

We\'re at a multi-million dollar run rate already having signed customers like Lovable and multiple neobanks. You\'ll be joining at the most exciting time - early enough that the equity can be life changing but at a point where demand has been proven.

IN THIS ROLE, YOU WILL

• Build from scratch and lead the Data Labeling team (hiring, coaching, and performance management)
• Define annotation guidelines, quality standards, and evaluation frameworks
• Develop quality assurance processes, calibration sessions, and auditing systems
• Partner with AI researchers and engineers to translate research objectives into labeling workflows
• Prioritise labeling projects based on business and research needs
• Monitor operational metrics including quality, consistency, throughput, and cost
• Improve annotation tooling, automation, and workflow efficiency
• Lead complex AI evaluation projects, including safety, preference ranking, RLHF, policy evaluation, and benchmark creation
• Analyse disagreement patterns and edge cases to improve guidelines and model performance
• Manage vendor relationships and ensure consistent quality across distributed teams
• Build reporting dashboards and communicate operational insights to leadership
• Foster a culture of continuous improvement, accountability, and operational excellence

WE\'RE LOOKING FOR SOMEONE WHO

• Has experience leading data annotation or AI evaluation teams
• Has strong operational and people management skills
• Understands AI model evaluation, LLM behavior, and modern annotation workflows
• Can design scalable processes without sacrificing quality
• Communicates clearly across technical and non-technical teams
• Thrives in fast-moving startup environments

YOU MIGHT BE A GREAT FIT IF YOU

• Have managed annotation programs for LLMs, generative AI, or machine learning
• Have experience with RLHF, preference data collection, safety evaluations, or benchmark creation
• Have worked in Trust & Safety, AI Safety, Content Moderation, or ML Ops
• Have managed distributed or global annotation teams
• Have experience with vendor management and outsourcing operations

BONUS POINTS

• Familiarity with prompt engineering and AI safety policies
• SQL, Python, or data analysis experience
• Experience building internal annotation platforms or workflow automation
• Background in linguistics, cognitive science, machine learning, or data operations

Important note

This role involves overseeing projects that may include offensive, harmful, violent, sexual, or otherwise disturbing content.
You\'ll be responsible for ensuring reviewers have the tools, guidance, and support necessary to perform this work safely and consistently.

WHY WHITE CIRCLE

• Competitive compensation package, including equity
• Flexible time off
• Paid time off in line with your local regulations, no matter where you work from
• Work from Paris (hybrid) + relocation package
• Best medical insurance in France
• Learning and development support for courses, conferences, and opportunities to grow your skills
• All the hardware, tools, and services you need
• Covered subscriptions for AI agents and IDEs
• Team off-sites twice a year: we\'ve recently been to the Alps and to Saint-Tropez

PROCESS

1. Intro call with HR (30 min)
2. Take-home test assignment
3. Final conversation with our CEO (45 min)