AI-Driven Biometric Security Expert

1 week ago

Melbourne, Victoria, Australia beBeeBiometricSecurity Full time $150,000 - $200,000

Our Ideal Candidate

  • We are seeking an expert in machine learning to join our team as a Biometric Security Specialist.

Job Summary

The Biometric Security Specialist will be responsible for designing and developing liveness detection systems that utilize AI algorithms to differentiate between real and fake biometric data. The ideal candidate will have a strong understanding of machine learning frameworks such as TensorFlow, Keras, or PyTorch, and experience in developing deep learning models is essential.

Key Responsibilities

  • Liveness Detection System Design: Develop and design liveness detection systems that incorporate multimodal approaches such as facial recognition, fingerprint scanning, and iris recognition.
  • Deep Learning Model Development: Build and optimize deep learning models specifically for liveness detection. This involves selecting appropriate algorithms, conducting experiments, and optimizing model parameters to enhance accuracy and reliability.
  • Feature Engineering: Identify and extract features from biometric data that are crucial for detecting spoofing attempts. This includes texture analysis, motion-based detection, and 3D depth analysis.
  • Data Collection and Preprocessing: Collaborate with data scientists to collect, clean, and preprocess large datasets required for training liveness detection models. Ensure data integrity and suitability for model development.
  • 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. Validate models against various spoofing techniques to ensure robustness.

Requirements

  • Machine Learning Expertise: In-depth understanding of machine learning frameworks such as TensorFlow, Keras, or PyTorch.
  • Experience in developing deep learning models is essential.
  • Programming Skills: Proficiency in programming languages such as Python, Java, or R for model development and algorithm implementation.
  • Analytical Skills: Strong problem-solving abilities with a solid grasp of statistics, probability theory, and data analysis techniques.
  • Collaboration Skills: Ability to work effectively with cross-functional teams (including data scientists, software engineers, and product managers) to achieve common goals.
  • Bachelor's degree in Computer Science, Mathematics, or a related field.
  • Familiarity with anti-spoofing standards for biometrics such as NIST ISO/IEC 30107 or FIDO.
  • Innovative mindset with a passion for continuous learning and keeping up with the latest advancements in AI and machine learning technologies.

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