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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.
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