ML Research Engineer- Scale NLP & Semantic Retrieval (Hybrid)

Npv; Paris; Hybride; EUR 90 000 - 130 000; Plein temps

Avantages offerts par ce poste

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

Résumé du poste

White Circle is seeking ML Engineers to join its AI Safety team building policy enforcement and optimization layers for AI systems. Hybrid work from Paris or London, with relocation support after probation.

The role focuses on turning petabytes of unstructured text into structured insights, building scalable pipelines, and applying LLMs for labeling and diagnostics. You will work with engineering and research to align pipelines with production constraints, delivering self-serve datasets, data

Qualifications

• Strong Python and SQL, with production-grade pipeline engineering.
• Applied NLP/ML on real-world text: embeddings, clustering, topic modeling, semantic search, classification.
• Experience at scale: distributed processing and large-scale storage and querying.

Responsabilités

• Turn petabytes of unstructured text into a structured, explorable view across topics, clusters, segments, trends and anomalies.
• Build scalable representation pipelines: sampling, preprocessing, embeddings, 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.

Connaissances

Python

SQL

NLP/ML

Distributed processing

MLOps

Description du poste

White Circle is seeking ML Engineers to join its AI Safety team building policy enforcement and optimization layers for AI systems. Hybrid work from Paris or London, with relocation support after probation.

The role focuses on turning petabytes of unstructured text into structured insights, building scalable pipelines, and applying LLMs for labeling and diagnostics. You will work with engineering and research to align pipelines with production constraints, delivering self-serve datasets, data