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Machine learning • chatillon 92

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Machine Learning Engineer

The French SourcerParis, Île-de-France, France
Temps plein
Quick Apply

Take recommendation models from notebook to production, serving millions of users in real time.Machine Learning Engineer - Paris.Paris, France · Permanent · Hybrid working policy to be confirmed.Bu... Voir plus

Stage Machine Learning

La JavanessParis, Île-de-France, FR
Stage
Quick Apply

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Eka FinanceParis, France
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Learning & Development Manager

ORIENT EXPRESSParis, Île-de-France, France
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Accor & Orient Express are currently seeking an experienced Learning & Development (L&D) Manager to lead and champion the Orient Express teams in Corporate and Operations (Hotels and Tr... Voir plus

Machine Learning Engineer

Sia PartnersParis, France
CDI

Dans le but d’implémenter des modèles de Machine Learning pour nos clients, Sia recrute un(e) Machine Learning Engineer (MLE) rigoureux(se) et passionné(e) par la donnée, pour accompagner nos clien... Voir plus

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JEMSParis, France
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Stage de fin d'études - Consultant·e Machine Learning & AI Engineer (H/F)

WavestonePuteaux, Île-de-France, France
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Data & Intelligence Artificielle.Nos équipes interviennent sur l'ensemble de la chaîne de valeur :.Intelligence Artificielle Générative (LLM, RAG, Agents).Machine Learning & Deep Learning.D... Voir plus

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Collective.workParis, Paris, FR
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Crédit Agricole CIBMontrouge
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ingénieur IA - Paris, France (H/F) - Astek

AstekParis, France
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Concepteur(trice) Digital Learning / Learning Experience Designer F/H

RydgeLa Défense, France
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BreopleParis, Paris, FR
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Consultant(e) Senior Tarification IARD – CDI (H/F) - Nexialog

NexialogParis, France
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Financial Markets & Investments.Financial Control & Compliance.En rejoignant notre Business Unit Actuarial Services, vous interviendrez sur des missions variées et stratégiques :.Chez nos clients d... Voir plus

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Finaxys recrute un Développeur Python / CDI (H/F) - Finaxys

FinaxysParis, France
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Finaxys est un cabinet de conseil.Depuis plus de 15 ans, nous intervenons auprès des plus grandes institutions telles que.BNP Paribas, Crédit Agricole, Société Générale, AXA, Malakoff Humanis.IA, M... Voir plus

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Open-Source Machine Learning Engineer - EMEA Remote

Hugging FaceParis, Île-de-France, FR
Télétravail
Temps plein
Quick Apply

At Hugging Face, we're on a journey to democratize good AI.We are building the fastest growing platform for AI builders with over 11 million users who collectively shared over 4 million models, 1 m... Voir plus

Alternance Machine Learning Engineer / AI Research - Paris (F/H)

iscod alternanceParis, France

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Machine Learning Researcher / Engineer (Foundation Models)

PathwayParis, Île-de-France, FR
Télétravail
Temps plein
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AI Scientist – Traitement du Signal & Machine Learning

SILKHOM SASParis, Île-de-France, France
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Stage Ingénieur IA - Invivoo

InvivooParis, France
Stage

Créée en 2004, INVIVOO est le partenaire technologique et historique des institutions financières depuis plus de 20 ans.Nous mobilisons nos expertises technologiques et métiers au service de nos cl... Voir plus

 • Offre sponsorisée
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Machine Learning Engineer

Machine Learning Engineer

The French SourcerParis, Île-de-France, France
Il y a 4 jours
Type de contrat
  • Temps plein
  • Quick Apply
Description de poste

Take recommendation models from notebook to production, serving millions of users in real time.

Machine Learning Engineer - Paris

Paris, France · Permanent · Hybrid working policy to be confirmed

What you'd actually work on

  • Building and maintaining recommendation and ranking models used across core product surfaces
  • Owning the ML lifecycle from feature preparation and training to deployment and production monitoring
  • Designing offline evaluation methods that reflect the behaviour expected in production
  • Building training and retraining pipelines that can run reliably without manual intervention
  • Deploying models through scalable, low-latency production services
  • Designing A/B tests and defining the metrics used to assess model performance and business impact
  • Working with data engineers to make production features reliable, consistent, and available at the required frequency
  • Monitoring model performance, feature quality, drift, latency, and prediction distributions
  • Investigating differences between offline results and production behaviour
  • Improving model deployment, versioning, rollback, and reproducibility
  • Partnering with product teams to translate business objectives into measurable optimisation problems
  • Contributing to code reviews, automated testing, CI/CD, and ML engineering standards

Where it gets technically interesting

  • Serving real-time features and predictions within strict latency requirements
  • Maintaining consistency between offline training data and online production features
  • Automating retraining pipelines while keeping model versions, datasets, and experiments reproducible
  • Detecting model or feature drift before it has a significant impact on users
  • Designing A/B tests with appropriate metrics, sample sizes, and evaluation periods
  • Balancing model complexity and prediction quality against latency and infrastructure costs
  • Handling cold-start problems for new users, products, or categories
  • Rolling out new models safely, with clear monitoring and rollback mechanisms

What we're looking for

  • 3+ years of experience deploying and operating machine learning models in production
  • Strong Python skills and good software engineering practices
  • Practical experience with PyTorch, TensorFlow, or an equivalent ML framework
  • Experience building training, evaluation, and inference pipelines
  • Knowledge of recommendation, ranking, personalisation, or similar machine learning systems
  • Experience with model deployment, monitoring, versioning, and automated retraining
  • Understanding of feature engineering and the differences between offline and online feature processing
  • Experience designing or analysing controlled experiments and A/B tests
  • Ability to investigate performance issues across models, data pipelines, and production infrastructure
  • Experience using Git, code reviews, automated testing, and CI/CD
  • Confidence working with data engineering, platform, and product teams

You do not need to have worked with every tool in the stack, but you should have experience taking models beyond experimentation and operating them as production systems.

The company

A fast-growing digital marketplace with millions of monthly active users, several hundred employees, and a strong presence across Europe.

Machine learning is used across key product areas, including recommendation, ranking, and personalisation. The team is developing the infrastructure and engineering practices required to operate these models reliably at scale.

Health insurance, meal vouchers, and an equity plan.

Languages: Native or bilingual French and professional English.

A search run by The French Sourcer, recruitment built for technical teams.