Senior Real-Time Fraud ML Engineer

SurePay; Utrecht; Hybride; EUR 90 000 - 135 000; Plein temps

Avantages offerts par ce poste

Salary + benefits budget

Holidays

Hybrid work setup

MacBook Pro & iPhone

Travel covered

Pension plan

Culture of ownership

Fridays & meetups

Diverse team

Résumé du poste

SurePay is expanding its Fraud Risk Intelligence team in Utrecht. We seek a Senior ML Designer/Engineer to architect and scale an enterprise-grade ML platform handling sub-millisecond real-time processing, combining supervised models, anomaly detection, and rule-based engines.

You will bridge data science, engineering, and product leadership, shaping real-time data streams, feature stores, and robust MLOps workflows using AWS SageMaker and IaC.

Qualifications

• 8+ years of software engineering and MLOps experience.
• Proven track record bringing ML models to production at scale.
• Balance of software engineering, cloud infrastructure and data science literacy.
• Familiarity with fraud/AML risk platforms (welcome).

Responsabilités

• Product Discovery & Sparring: Partner with Data Scientists to connect implementations with client requirements and business context.
• Data Science Enablement: Guide packaging and deployment of ML models to production in a clean, modular way.
• API & Product Integration: Design high-performance microservice APIs with sub-millisecond latency.
• Data Platform Evolution: Shape real-time data streaming and online feature store management.
• MLOps & Infrastructure Ownership: Architect, deploy and maintain AWS MLOps infra using IaC and SageMaker.
• Model Emulation & Operations: Set up monitoring, drift detection and continuous training loops.

Connaissances

AWS & MLOps Infra

Production Python

Real-Time Data

ML Frameworks

Prototype & Iterate

System Resilience

Communication

Outils

PyTorch

TensorFlow

Scikit-learn

Apache Spark

AWS SageMaker

Terraform

Description du poste

SurePay is expanding its Fraud Risk Intelligence team in Utrecht. We seek a Senior ML Designer/Engineer to architect and scale an enterprise-grade ML platform handling sub-millisecond real-time processing, combining supervised models, anomaly detection, and rule-based engines.

You will bridge data science, engineering, and product leadership, shaping real-time data streams, feature stores, and robust MLOps workflows using AWS SageMaker and IaC.