Machine Learning Engineer (Deepfake & Injection Attack Detection / Face Liveness)
Core
Design, train, and deploy machine learning models for image-based fraud detection, specifically deepfake detection, injection attack detection, and digital manipulation analysis in selfie-based identity verification.
Role type
Senior IC machine learning engineer (deepfake & injection attack detection)
Builds
Production ML systems for fraud & AI integrity in digital identity verification
Domain
Digital identity verification, biometrics, fraud prevention
Deliverable
production ML models
Required skills
Computer vision (image-based ML), Python, PyTorch, TensorFlow, data pipeline construction, dataset curation, model evaluation, adversarial ML concepts
Preferred skills
PhD or equivalent in ML/CV, fraud detection domain experience, deepfake detection/image forensics, generative AI model analysis, data science or data engineering background
Technologies
AWS, Docker, CI/CD, Pandas, OpenCV, Scikit-learn
Responsibilities
Design and train ML models for deepfake and injection attack detection; curate large-scale adversarial datasets; build robust data pipelines with validation and cleaning; define evaluation frameworks for precision/recall trade-offs; collaborate with research, MLOps, and product teams; monitor production model performance and scalability.
Seniority
Senior, hands-on IC
