machine learning engineer for AI Engines

Qonto provides SMEs with a finance workspace centered on banking and enhanced with financial tools. Its financial services operate across eight European countries.

• Develop machine learning models end-to-end, from understanding product requirements through training, evaluation, and production deployment
• Integrate machine learning models into Qonto’s financial services in collaboration 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 in production and ensure quality assurance and continuous monitoring
• Share best practices, improve internal tools, and mentor peers across the ML team

• 6+ Years as an ML Engineer with ML Ops experience
• Experience developing and deploying end-to-end, customer-facing ML products with measurable impact on real users; experience with internal tools or dashboards alone does not meet this requirement
• Experience building and optimising machine learning models for external customers, and knowing when to use Generative AI versus proven ML techniques
• Strong Python engineering skills, including writing resilient, testable code at scale
• Proficiency with FastAPI or similar, third-party service integration, and database interaction in production
• Familiarity with tools for automated model retraining, performance checking, and drift detection
• Experience building or significantly improving ML infrastructure
• Fluent English

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