ML Research Engineer

Npv · Paris, London · posted Sep 22, 2026

Open to candidates in France and United Kingdom

Full-timemidAI Safety

What this role actually asks for

Extracted by RemoteHunt

Must have

  • Production-grade Python and SQL pipeline engineering
  • Applied NLP/ML on real-world text
  • Experience with large-scale data processing
  • Evaluation of fuzzy problems
  • Experience with safety/moderation datasets

Nice to have

  • Public builder footprint (open-source, papers)
  • Experience at a frontier lab
  • RL for LLMs beyond RLHF
  • Multilingual model training

Tools and technologies

PythonSQLLLMsembeddingsclusteringtopic modelingsemantic searchclassificationRL

Worth checking before you apply

  • hybrid

The full posting

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.

Is this one actually worth your time?

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