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    ML Research Engineer

    Original title · English translation pending

    NpvParisPosted 2026-09-23Last seen in source
    Location
    Paris
    Employment
    Full Time
    Workplace
    On-site
    White Circle
    Apply via Arbeitnow

    Role description

    Original description · English translation pending

    We're looking for ML Engineers to join White Circle, an AI Safety company building the policy enforcement and optimization layer for AI systems. Backed by $11M from senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, and DeepMind, White Circle processes 100M+ API calls monthly and runs its own LLMs in production.

    You will

    • Turn petabytes of unstructured text into a structured, explorable view: topics, clusters, segments, trends, anomalies.
    • Build scalable representation pipelines: sampling, preprocessing, embeddings at scale, indexing, and retrieval.
    • Use LLMs for labeling, weak supervision, data enrichment, and automated diagnostics, with cost/quality controls.
    • Translate findings into product and operational decisions, and ship self-serve datasets, data models, and dashboards.
    • Work with engineering and research to align pipelines with production constraints (latency, cost, privacy).

    Requirements

    • Strong Python and SQL, with production-grade pipeline engineering (not just notebooks).
    • Applied NLP/ML on real-world text: embeddings, clustering, topic modeling, semantic search, classification.
    • Experience at scale: distributed processing, large-scale storage and querying, performance-cost tradeoffs.
    • Evaluation of fuzzy problems: offline/online metrics, human-in-the-loop labeling, inter-annotator agreement, drift monitoring.
    • Prior work with safety/moderation datasets, policy/rule systems, or high-volume logging/observability.
    • Relocation to Paris or London (hybrid) required.

    Bonus

    • Public builder footprint: open-source models, datasets, or frameworks on HuggingFace/GitHub, papers, or technical posts.
    • Experience at a frontier or near-frontier lab, or leading open-source model releases.
    • RL for LLMs beyond standard RLHF: online RL, GRPO-style methods.
    • Moderation, safety, or classification models at scale; multilingual model training.

    We offer

    • Competitive salary + equity.
    • Hybrid work from central London or Paris office, relocation support for Paris after probation.
    • Premium private health insurance, mental health support, flexible time off.
    • Lunch and dinner covered in the office, L&D budget, all hardware and tools you need.
    • Team off-sites twice a year.

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