Fraud Detection ML Engineer - Real-time, Hybrid (Spain)

The French Sourcer; Madrid; Hybrid; EUR 65,000 - 95,000; Full time

Benefits offered by this job

Health insurance

Flexible working

Equity plan

Job summary

The French Sourcer in Spain (Madrid or Barcelona) seeks a Machine Learning Engineer for a permanent, hybrid role focused on fraud detection in live transactions.

You will build features from transactional and behavioural data, deploy models with low latency, monitor performance, and collaborate with risk, data engineering, platform, and product teams to balance detection with customer experience.

Qualifications

• 3+ years of experience developing applied machine learning models.
• Strong Python skills and good software engineering practices.
• Experience deploying and operating models in production.
• Knowledge of classification, anomaly detection, or risk-scoring methods.
• Experience with imbalanced datasets and appropriate evaluation metrics.
• Understanding of precision, recall, false-positive rates, and the business trade-offs between them.
• Experience with model monitoring, drift detection, versioning, and retraining.
• Ability to work with large transactional or behavioural datasets.
• Experience with low-latency inference systems.
• Confidence working with risk, data engineering, platform, and product teams.
• Experience using Git, code reviews, automated testing, and CI/CD.

Responsibilities

• Build and maintain fraud detection and risk-scoring models used on live transactions.
• Develop features from transactional, behavioural, account, and device data.
• Train and evaluate models against evolving fraud patterns.
• Deploy models into low-latency production systems.
• Reduce false positives while preserving detection rates.
• Collaborate with risk specialists to translate fraud rules into model features.
• Design feedback loops using confirmed fraud cases and transaction outcomes.
• Monitor model performance, drift, latency, and distribution.
• Investigate model degradation and changes in customer or fraud behavior.
• Improve deployment, versioning, retraining, and rollback processes.
• Document model behaviour and decisions for engineers, risk teams, and auditors.
• Contribute to code reviews, automated testing, CI/CD, and ML engineering standards.

Skills

Python

ML model development

Low-latency inference

Tools

Git

CI/CD

Job description

The French Sourcer in Spain (Madrid or Barcelona) seeks a Machine Learning Engineer for a permanent, hybrid role focused on fraud detection in live transactions.

You will build features from transactional and behavioural data, deploy models with low latency, monitor performance, and collaborate with risk, data engineering, platform, and product teams to balance detection with customer experience.