Senior Biometric Security Specialist

7 days ago

Melbourne, Victoria, Australia beBeeBiometrics Full time $120,000 - $160,000
Job Title

About the Business:

We are a leading provider of risk assessment solutions.

We offer a range of services focused on helping businesses drive higher revenue growth, maximize operational efficiencies, and improve customer experience.

Our solutions help our customers solve difficult problems in areas such as Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management.

The role involves utilizing machine learning and deep learning techniques to create models capable of distinguishing between genuine human interactions and fraudulent attempts.

Responsibilities:

Liveness Detection System Design: Develop and design liveness detection systems that utilize AI algorithms to differentiate between real and fake biometric data.

This includes analyzing facial features, eye movements, and other physiological indicators.

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.

This includes 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.

Validate models against various spoofing techniques to ensure robustness.

Maintenance and Support: Deploy liveness detection systems into production environments, ensuring scalability and high performance.

Continuously monitor system outputs to identify any issues with accuracy or efficiency.

Required Skills and Qualifications:

  • 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.
  • Experience in similar roles focusing on anti-spoofing or biometric security systems.
  • 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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