SENIOR MACHINE LEARNING ENGINEER (APPLIED SCIENTIST DOCUMENT FRAUD)

About the role

The Senior Machine Learning Engineer (Applied Scientist – Document Fraud) will own document‑fraud R&D, designing and deploying anti‑spoofing methods, creating features, training models, extending the ML platform, guiding engineers and collaborating with CV specialists to deliver both short‑term and long‑term verification capabilities.

About the company

ALiCE Biometrics is a spin‑off from the Gradiant R&D Technology Center that provides a biometric identity verification solution for online onboarding, using deep‑learning face recognition and passive liveness detection to reduce identity fraud and improve conversion.

Requirements

• PhD in Computer Science or related quantitative field, or MS with relevant experience
• 5+ years building production machine‑learning systems and solving real‑time problems
• Strong academic and publication record
• Experience with cloud‑based training and deployment pipelines
• Experience training neural‑net architectures for classification, object detection and segmentation
• Excellent Python coding skills; C++ a plus
• Proficiency with OpenCV, TensorFlow/Keras, TensorRT, PyTorch (and FastAI); strong portfolio of projects
• Familiarity with transformer frameworks such as BERT is a plus
• Good working knowledge of Git, Google AI Cloud, Docker, Kubernetes; Linux, Redis, ELK stack a plus
• Solid understanding of statistics, probability, linear algebra and calculus
• Hands‑on experience in computer‑vision projects such as face verification, object detection or classification
• Ability to read, discuss and apply research from published papers
• Strong communication skills to translate complex ideas into understandable content
• Pro‑active, self‑managing attitude