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Biometric Authentication Specialist Job Description
The ideal candidate for this challenging role will have in-depth knowledge of machine learning frameworks such as TensorFlow, Keras, or PyTorch. You will be responsible for developing advanced systems to detect and prevent spoofing attacks during biometric authentication processes.
Key Responsibilities:
- Liveness Detection System Design: Develop and design liveness detection systems that utilize AI algorithms to differentiate between real and fake biometric data.
- Deep Learning Model Development: Build and optimize deep learning models specifically for liveness detection.
- Feature Engineering: Identify and extract features from biometric data that are crucial for detecting spoofing attempts.
- Data Collection and Preprocessing: Collaborate with data scientists to collect, clean, and preprocess large datasets required for training liveness detection models.
- Algorithm Implementation: Implement machine learning algorithms capable of processing real-time biometric data to detect inconsistencies indicative of spoofing attempts.
- System Testing and Validation: Conduct rigorous testing of liveness detection systems to ensure performance in real-world scenarios.
- Monitoring and Maintenance: Deploy liveness detection systems into production environments, ensuring scalability and high performance.
Requirements:
- Bachelor's degree in Computer Science, Mathematics, or a related field.
- Familiarity with anti-spoofing standards for biometrics such as NIST ISO/IEC 30107.
We welcome applications from diverse candidates who possess strong technical skills, analytical thinking, and the ability to collaborate effectively with cross-functional teams.
