[Hiring] Machine Learning Engineer (Deepfake & Injection Attack Detection / Face Liveness ) @Mitek Systems

Role Description

As a Machine Learning Engineer, you will join our Fraud & AI Integrity group, specifically focused on deepfake detection, digital manipulation, and injection attack detection in selfie-based identity verification. This is a hands-on, production-focused role.

What You Will Do (Core Responsibilities):

• Design, train, and deploy machine learning models for image-based fraud detection, including:
  • Deepfake detection
  • Injection attack detection
  • 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, and 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
  • Product teams
• Contribute to production ML systems, ensuring:
  • Scalability and reliability
  • Monitoring and performance tracking
  • Continuous improvement against evolving threats

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field
• 2+ years of experience deploying machine learning models into production
• Strong background in computer vision (image-based ML)
• Solid programming skills in Python
• Hands-on experience with PyTorch and/or TensorFlow
• Experience working with real-world datasets and building data pipelines

Requirements

• Tech Stack:
  • Cloud: AWS
  • Languages: Python
  • ML Frameworks: PyTorch, TensorFlow, Scikit-learn
  • Data Tools: Pandas, OpenCV
  • Infrastructure: Docker, CI/CD, cloud-based ML pipelines

Benefits

• Competitive package
• Full Remote contract
• Annual Leave
• Home Office Allowance
• Annual Bonus – up to 10%
• Health Insurance
• Learning & Development:
  • We promote continuous learning and support role-aligned development opportunities, with access to a complimentary LinkedIn Learning licence.
• €50,000 - €62,000 a year
• Working Model:
  • Remote within Spain
  • Occasional in-person collaboration (weekly or biweekly is a plus)