Machine Learning Engineer (Cataluña)

What You Will Do (Core Responsibilities)

• Design, train, and deploy machine learning models for image-based fraud detection, including deepfake detection, injection attack detection, and digital manipulation analysis in biometric verification.
• Work end-to-end across the ML lifecycle: dataset curation (large-scale, noisy, adversarial datasets), model development and training, evaluation and iteration using fraud-relevant metrics, production deployment and monitoring.
• Build robust data pipelines, including data validation, cleaning, labeling strategies, handling class imbalance, bias, and distribution shift.
• Define and execute evaluation frameworks focused on real‑world performance: precision/recall trade‑offs, false positive vs. fraud detection balance, robustness to unseen attack types.
• Collaborate closely with Fraud & AI research teams, data collection and annotation teams, MLOps and platform engineering, and product teams to cont...