Senior Data Labeler

White Circle; Paris; Hybride; EUR 70 000 - 110 000; Plein temps

Avantages offerts par ce poste

Equity

Flexible time off

Office in Paris (2nd arrondissement)

Relocation support

Private health insurance

Mental health support

Language lessons

Lunch and dinner provided

Learning & development

Tools & equipment

Team off-sites

Résumé du poste

White Circle in Paris is seeking a Data Labeling Lead to build our annotation team from the ground up, setting quality standards, evaluation frameworks, and the labeling operations behind our safety evals, RLHF, and benchmarks.

You will own quality, throughput, and cost while collaborating with AI researchers to translate research goals into scalable labeling workflows and to manage vendor relationships and dashboards for leadership.

Qualifications

• Experience leading data annotation or AI evaluation teams.
• Strong operational and people management skills.
• Understanding of AI model evaluation, LLM behavior, and annotation workflows.
• Ability to design scalable processes without sacrificing quality.
• Excellent communication across technical and non-technical teams.

Responsabilités

• Build from scratch and lead the Data Labeling team (hiring, coaching, 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, throughput, and cost.
• Improve annotation tooling, automation, and workflow efficiency.
• Lead complex AI evaluation projects, including safety, RLHF, and benchmarks.
• Analyze disagreement patterns 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 and accountability.

Connaissances

Data labeling leadership

People management

AI evaluation

Annotation workflows

Process design

Clear communication

Description du poste

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.

About us

White Circle 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 recently raised our Series A funding round, taking our total funding to $70M. Our investors include 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 behaviour, 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.

Compensation & benefits

• Competitive compensation, including equity

• Flexible time off

• A spacious office in the heart of Paris’s 2nd arrondissement, with a flexible hybrid setup

• Relocation support if you’re moving to Paris, available after your probationary period

• Premium private health insurance

• Mental health support, including coverage for therapy when you need it

• Language lessons to help you improve your English or French

• Lunch and dinner covered when you work from the office

• Learning and development support for courses, conferences, and opportunities to grow your skills

• All the hardware, subscriptions, tools, and services you need

• Team off-sites twice a year: we’ve recently been to the Alps, Saint-Tropez, and Marbella

Process

1. Intro call (25 min)

2. Take-home test assignment

3. Final conversation with CEO (45 min)