ML Researcher for Contactless Fingerprint Authentication

We are looking for a highly skilled Machine Learning Researcher to work on an innovative Contactless Fingerprint Authentication solution. The project focuses on developing AI/ML models capable of recognizing and authenticating fingerprints captured through mobile cameras or contactless imaging systems. The ideal candidate should have strong expertise in computer vision, deep learning, biometric authentication, and image processing. Key Responsibilities Research and develop ML/DL models for contactless fingerprint recognition and authentication. Work on fingerprint image enhancement, preprocessing, segmentation, and feature extraction. Develop matching and verification algorithms for biometric authentication. Train and optimize deep learning models using frameworks such as TensorFlow or PyTorch. Improve accuracy under varying lighting, angles, blur, and image quality conditions. Conduct experiments, benchmarking, and performance evaluation. Collaborate on integrating models into real-world applications or APIs. Required Skills Strong experience in Machine Learning and Deep Learning. Expertise in Computer Vision and Image Processing. Experience with biometric systems or fingerprint recognition is highly preferred. Proficiency in Python. Hands-on experience with: TensorFlow / PyTorch OpenCV CNN architectures Feature extraction and image matching techniques Understanding of authentication systems and model optimization. Preferred Qualifications Prior work in contactless biometrics or fingerprint authentication. Experience with mobile vision systems or camera-based recognition. Research background or published work in biometrics/computer vision is a plus. Familiarity with edge AI or lightweight model deployment. Deliverables Trained ML model(s) Research findings and documentation Performance evaluation metrics Prototype/demo for fingerprint authentication workflow

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