Senior Real-Time Fraud ML Engineer

SurePay; Utrecht; Hybrid; EUR 95,000 - 130,000; Full time

Benefits offered by this job

Hybrid work setup

MacBook Pro / iPhone

Travel costs covered

Pension plan

8% personal benefits budget

Job summary

SurePay is expanding its Fraud Risk Intelligence domain and building an enterprise‑grade ML platform. You will join a focused cross‑functional team to develop real-time ML processing infrastructure and product APIs with sub‑millisecond latency.

The role emphasizes productionizing ML models, AWS MLOps, and scalable data pipelines, with a strong emphasis on collaboration across Data Science, Data Engineering, and Product Leadership.

Qualifications

• 8+ years in software engineering and MLOps.
• Experience bringing ML models to production at scale.
• Experience with AWS SageMaker, IaC, and CI/CD pipelines for ML.

Responsibilities

• Product Discovery & Sparring: partner with Data Scientists to translate requirements into production plans.
• Data Science Enablement: guide packaging and deployment of ML models for production in a modular way.
• API & Product Integration: design high-performance APIs with sub-millisecond latency for ML models.
• Data Platform Evolution: shape real-time data streaming and online feature store management.
• MLOps & Infrastructure Ownership: implement end-to-end AWS MLOps via IaC and CI/CD.
• Model Emulation & Operations: set up monitoring, drift detection, and continuous training loops.

Skills

AWS MLOps

Python

Microservices

Real-time data

ML Frameworks

CI/CD for ML

Terraform

Communication

Cross-functional

Tools

PyTorch

TensorFlow

Scikit-learn

Apache Spark

AWS SageMaker

Job description

SurePay is expanding its Fraud Risk Intelligence domain and building an enterprise‑grade ML platform. You will join a focused cross‑functional team to develop real-time ML processing infrastructure and product APIs with sub‑millisecond latency.

The role emphasizes productionizing ML models, AWS MLOps, and scalable data pipelines, with a strong emphasis on collaboration across Data Science, Data Engineering, and Product Leadership.