machine learning engineer in fintech in Berlin

Описание

Qonto provides Europe's leading finance workspace for SMEs, with banking at its core and additional financial tools. Its AI team builds customer-facing AI products for business customers in financial services.

Задачи

• Develop machine learning models end-to-end, from understanding product requirements through training, evaluation, and production deployment
• Integrate machine learning into the product ecosystem with Product Managers, Data Engineers, and Backend Engineers
• Build the ML Ops framework, including model drift detection, performance tracking, automated retraining pipelines, monitoring, and alerts
• Put models into production with robust technical implementation, quality assurance, and continuous monitoring
• Share best practices and contribute to internal tooling improvements
• Mentor peers across the ML team

Требования

• 6+ Years of experience as an ML Engineer with ML Ops experience
• Experience developing and deploying client-facing ML products end-to-end with measurable impact on real users
• Experience building and optimising machine learning models for external customers
• Ability to choose between Generative AI and proven machine-learning techniques
• Strong Python engineering skills and experience writing resilient, testable code at scale
• Proficiency with FastAPI or similar frameworks, third-party service integration, and database interaction in production
• Experience with tools for automated model retraining, performance checking, and drift detection
• Experience building or significantly improving ML infrastructure
• Fluent English

Условия

• Customer-facing AI products used by hundreds of thousands of business customers
• Modern stack including Python, Snowflake, Kafka, Kibana, PostgreSQL, Airflow, AWS, Prometheus, ArgoCD, GitHub, and Cursor
• Freedom to test tools that help reach the target
• Team of 10 AI Engineers and 3 Data Ops specialists
• Individual contributor career path with access to the latest AI technologies
• The hiring process lasts 20 working days on average