Staff Machine Learning Engineer – AI Engines

🕒 May 20

🌐 France, Spain, +2 more countries – Remote

🇫🇷 France – Remote 🇪🇸 Spain – Remote 🇮🇹 Italy – Remote 🇩🇪 Germany – Remote

⏰ Full Time

🔴 Lead

🤖 AI Engineer

👻 Ghost score 55%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Qonto

WebsiteLinkedInAll Job Openings

501 - 1000 employees

💳 Fintech

🤝 B2B

🏦 Banking

💰 $500k Grant on 2022-10

Fintech • B2B • Banking

Qonto is the leading European business finance solution that simplifies everything from everyday banking and financing to bookkeeping and spend management. Founded in July 2017 by Alexandre Prot and Steve Anavi, Qonto aims to energize SMEs and freelancers so that they can achieve more. With over 300,000 companies using its services and a workforce of around 900 employees, it stands out in the financial services sector as an innovative fintech solution.

📋 Description

• Build and ship customer-facing AI for 600,000+ business customers • Develop ML models end-to-end, from product requirements through training, evaluation, and production deployment • Integrate ML models into Qonto's financial services with Product Managers, Data Engineers, and Backend Engineers • Build ML Ops infrastructure for model drift detection, performance tracking, automated retraining pipelines, monitoring, and alerts • Implement models robustly with quality assurance and continuous production monitoring • Share best practices and improve internal tooling • Mentor peers across the ML team

🎯 Requirements

• 6+ years as an ML Engineer with ML Ops experience • Experience developing and deploying client-facing ML products end-to-end • Experience building and optimising machine learning models for external customers • Knowledge of when to use Generative AI versus proven machine-learning techniques • Strong Python engineering skills • Proficiency with FastAPI or similar, third-party service integration, and database interaction in production • Familiarity with automated model retraining, performance checking, and drift detection tools • Experience building or significantly improving ML infrastructure • Fluent in English

🏖️ Benefits

• Unlimited access to the best AI tools • Customer-facing AI with measurable impact and adoption metrics • Modern, flexible technology stack • Freedom to test tools that help reach the target • Individual contributor career path • Access to the latest AI technologies