Bachelor's / Master's / PhD in Computer Science, AI,
Electrical Engineering, or related fields.
3+ years of experience in computer vision / face recognition / liveness detection / anti-spoofing.
Proven track record of deploying vision models to production, ideally on mobile / edge platforms.
Strong programming skills in Python; familiarity with frameworks like PyTorch, TensorFlow, ONNX, and mobile inference frameworks.
Experience with face detection, face alignment, landmark detection, preprocessing, and image normalization workflows.
Experience in liveness detection methods: texture / reflection / depth cues / motion cues / multimodal approaches.
Experience optimizing models (quantization, pruning, knowledge distillation) for deployment under resource constraints.
Strong problem solving, debugging, and analytical skills.
Good communication skills; ability to explain trade offs to product, mobile, and operations teams.