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AI trust & safety jobs — ML | Ledger | Paris · Ganloss

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AI role · Open offer

ML Engineer — détection fraude crypto

Ledger

Permanent (CDI)
Full-time
Senior
Trust & safety ML
Hybrid
1 Rue du Mail, Paris, IDF 75002, France · Hybrid
Paris, France
EUR 65k–90k/year + BSPCE

This listing is optimized for AI-native talent: clear skills and tools so candidates know if they fit before they apply—and so you spend less time screening mismatches.

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At a glance

How you'll work, where, and key listing dates.

Employment: Permanent (CDI), Full-time
Workplace: Hybrid
Location: 1 Rue du Mail, Paris, IDF 75002, France · Hybrid
Compensation: EUR 65k–90k/year + BSPCE
Experience level: Senior
Team: Trust & safety ML
Benefits & perks: BSPCE, produit hardware + software, hybrid Paris 2e.
How to apply: Modèle fraude temps réel ou graphe avec métriques précision/rappel.
Company site: www.ledger.com
Listed: Jun 6, 2026
Updated: Aug 3, 2026

About this role

What the team is looking for and how this position fits.

Ledger is hiring a Senior ML Engineer — détection fraude crypto on the Trust & safety ML team (Hybrid · Paris, France). This is a hands-on role in risk & decision ML—not a generic “AI enthusiast” post.

You will own real-time scoring, monitoring, and governance end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.

Ledger sécurise des millions de portefeuilles crypto — détection fraude et confiance utilisateur depuis Paris.

ML Engineer fraude (hybride Paris 2e) : modèles temps réel, graphes de transactions et alerting sur schémas adversariaux.

À propos de Ledger

Licorne française hardware + software web3.
Équipes ML trust & safety à Paris.
Volume transactions et contraintes latence strictes.

Missions

Entraîner classifieurs fraude avec features graphe.
Déployer scoring sub-seconde avec monitoring drift.
Collaborer avec analystes fraude sur boucles feedback.

Stack & environnement

Python, PyTorch, Kafka, SQL, feature store.
Hybride Paris 2e.

Profil recherché

4+ ans ML en fraude, risk ou trust & safety.
Éligibilité travail en France.

Skills we're hiring for

What each capability means for this role—not a keyword checklist.

Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
PyTorch
Training and inference with PyTorch: reproducible experiments, checkpointing, and deployment-minded exports.
SQL
Analytical SQL for features, cohorts, label quality, and experiment analysis at scale.
Machine Learning
Practical Machine Learning experience applied to real-time scoring, monitoring, and governance in production or rigorous pilots.

Tools & stack

Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).

KafkaTool
Streaming features or scores with ordering, idempotency, and monitoring for real-time systems.

You're a strong fit if…

Tailored to this listing—use it as a self-check before you apply.

You can show evidence in your application: Modèle fraude temps réel ou graphe avec métriques précision/rappel.
Several of these show up in recent shipped work—not only on your CV: Python, PyTorch, SQL, Machine Learning, and Kafka.
You have owned real-time scoring, monitoring, and governance in production: debugging live issues, running postmortems, and iterating from real user or business signals.
You are comfortable with the hybrid rhythm (Hybrid · Paris, France)—onsite collaboration when it matters, deep work when remote.
You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.
You read the full listing (comp: EUR 65k–90k/year + BSPCE, benefits in At a glance) and your expectations align.

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What the employer asked for

Modèle fraude temps réel ou graphe avec métriques précision/rappel.

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ML Engineer — détection fraude crypto

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ML Engineer — détection fraude crypto

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