Requirements

7+ years of experience as an engineer working in the machine learning domain
Strong Python programming skills
Experience with the full machine learning model lifecycle in production environments
Experience leveraging big data to create pipelines to feed models with appropriate data
Strong understanding of software engineering practices, data engineering, and MLOps principles
Knowledge of data science, statistics, and machine learning techniques
Familiarity with Python data science toolkits such as (Py)Spark, (Trino) SQL, Tensorflow, PyTorch, XGBoost/LightGBM, Pandas, MLFlow or similar MLOps frameworks, and Airflow
Experience with ML infrastructure tools such as Kubernetes, Docker, Airflow, Argo Workflows, Prometheus, and Grafana
Experimental mindset with a launch fast and iterate mentality
Proactive leadership in projects from ideation to deployment with strong communication skills across stakeholders

Nice to Haves

Develop and maintain production ML pipelines for data ingestion, training, validation, and deployment
Upgrade an existing rules-heavy system to a modern automated AI/ML detection engine
Collaborate with data engineers and analysts to develop best-in-class fintech models
Work with operations and compliance teams to ensure models operate smoothly worldwide
Tackle technical challenges like extreme class imbalance and incomplete ground truth
Support and encourage good engineering practices within the team

Opportunity to work on complex technical challenges at scale in a fast-growing fintech environment
Supportive culture enabling ownership of career development
Diverse, inclusive, and equitable workplace encouraging you to be your true self
Full-time position based in Amsterdam with relocation support if applicable
Committed to a smooth, flexible, and respectful candidate experience