White Circle fournit aux entreprises une plateforme qui teste, surveille et contrôle le comportement des modèles et agents d’IA. Elle aide les équipes de sécurité à détecter les risques, les fuites de données et les actions malveillantes.
Senior Data Labeler
Am I a fit — voir ma compatibilitéWhite Circle recherche un Senior Data Labeler pour créer et diriger son équipe de labellisation de données à Paris. Le poste couvre la définition des standards d’annotation, l’évaluation de modèles d’IA, le suivi de la qualité et l’amélioration des processus. L’environnement de travail est hybride, avec des projets portant notamment sur la sécurité de l’IA, le RLHF et les classements de préférences.
Repères sur White Circle
- Secteur
- Logiciels et Internet
- Siège
- Paris
- Domaine officiel
- whitecircle.com
- Dernière levée
- Seed · 2026-05-01
- Montant annoncé
- 11 000 000 $
- Offres ouvertes
- 11
Investisseurs mentionnés
Détails de l’offre
La description complète publiée par White Circle.
About us
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 salary + equity
- Work from Paris (hybrid) with a relocation package available, or work from London (note: we are currently unable to provide relocation support and medical insurance for London-based roles)
- Paid time off in line with your local regulations
- 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 Saint-Tropez HOW WE HIRE
- Intro call with HR (30 min)
- Take-home exercise
- Final conversation with our CEO (45 min) Please submit your application in English.
Prérequis
- leading data annotation or AI evaluation teams
- operational and people management skills
- AI model evaluation
- LLM behavior
- modern annotation workflows
- RLHF
- preference data collection
- safety evaluations
- benchmark creation
- vendor management
- outsourcing operations
Avantages mentionnés
- equity
- relocation package
- paid time off
- hardware, tools, and services
- AI agents and IDEs subscriptions
- team off-sites