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Senior Advanced Systems Developer

3 weeks ago

Melbourne, Victoria, Australia beBeeBiometric Full time $180,000 - $250,000
Advanced Biometric Security Specialist

This is a challenging opportunity to develop cutting-edge systems that can detect and prevent spoofing attacks during biometric authentication processes.

Key Responsibilities:
  • Liveness Detection System Design: Develop advanced liveness detection systems utilizing AI algorithms to differentiate between real and fake biometric data, ensuring the highest level of security for biometric authentication systems.
  • Deep Learning Model Development: Build and optimize deep learning models specifically for liveness detection, selecting appropriate algorithms, conducting experiments, and optimizing model parameters to enhance accuracy and reliability in detecting spoofing attempts.
  • Feature Engineering: Identify and extract critical features from biometric data necessary for detecting spoofing attempts, including 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, ensuring 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, integrating multimodal approaches such as facial recognition, fingerprint scanning, and iris recognition.
  • System Testing and Validation: Conduct rigorous testing of liveness detection systems to ensure performance in real-world scenarios, validating models against various spoofing techniques to guarantee robustness.
  • Monitoring and Maintenance: Deploy liveness detection systems into production environments, ensuring scalability and high performance, continuously monitoring system outputs to identify any issues with accuracy or efficiency.
Requirements:
  • Machine Learning Expertise: In-depth understanding of machine learning frameworks such as TensorFlow, Keras, or PyTorch, experience in developing deep learning models essential for this role.
  • 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.
  • Experience in Similar Roles: Previous experience in similar roles focusing on anti-spoofing or biometric security systems is highly desirable.