About the role
Build and maintain ML models for transaction monitoring at SumUp.
- •Join the AI AML Engineering Squad at SumUp to build and maintain ML models for transaction monitoring.
- •Key Responsibilities Build, maintain, and improve ML models and batch training pipelines for AML transaction monitoring.
- •Engineer Feature Store features mapped to AML typologies and suspicious behaviours.
- •Run sensitivity tests on synthetic datasets, produce ML governance artefacts, and deliver audit-ready documentation.
- •Own and evolve the AML Risk Score by analysing driver contributions, monitoring drift, running back-testing, and recommending improvements.
- •Partner with AML Operations, Product, and Engineering to translate stakeholder needs into actionable, scalable data science solutions.
- •Requirements Strong Python skills with hands-on data engineering experience and a proven track record of building reliable, production-grade ML workflows.
- •Experience in feature engineering and unsupervised machine learning, with the ability to translate domain knowledge into model behaviours and alerting logic.
- •Proven ability to productionalise ML applications and operate end-to-end pipelines, including monitoring, versioning, and rollback in regulated environments.
- •Comfort working across complex, multi-source data ecosystems where data quality, lineage, and root-cause analysis require careful attention.
Tech stack
PythonMLflowKubeflowSageMakerVertex AIONNXJAXPandasNumPyscikit-learnApache KafkaApache FlinkPostgreSQLMySQLMongoDBRedisElasticsearchDynamoDBCassandraSQLiteOracleSQL ServerNeo4jCockroachDBTimescaleDBInfluxDBSupabaseFirebasePrismaAWS
Match insights
Tech:Python, MLflow, Kubeflow, SageMaker, Vertex AI
Level:Senior