About Qonto
Qonto provides SMEs with a finance workspace centered on banking and enhanced with financial tools. Its financial services operate across eight European countries.
Responsibilities
•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
Requirements
•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
Conditions
No conditions stated in the posting.
