Consulting/Principal Software Engineer at LexisNexis Risk Solutions

Consulting/Principal Software Engineer

Would you like to be part of a team that delivers high-quality software to our customers?

Are you a highly visible champion with a ‘can do’ attitude and enthusiasm that inspires others?

About the Business

LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our government vertical, our solutions assist government agencies and law enforcement to drive insights from complex data sets, improving operation efficiency, increasing program integrity, discovering, and recovering revenue, and making timely and informed decisions to enhance investigations. You can learn more about LexisNexis Risk at the link below. Government Data, Analytics & Linking Technology|LexisNexis Risk Solutions

About the Team

IDVerse A LexisNexis® Risk Solutions Company is an identity verification software company that has developed world leading digital identity verification technology. We’ve built everything from the ground up and have a broad range of blue-chip customers across banking, telecommunications, government and more. We’ve perfected the technology in Australia and New Zealand and are in the process of rapidly expanding the reach of our industry leading technology globally.

About the Role 

The Anti-Spoofing/Liveness Detection Engineer focuses on developing advanced systems to detect and prevent spoofing attacks during biometric authentication processes. This 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 ivolves 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.

• Monitoring and Maintenance: Deploy liveness detection systems into production environments, ensuring scalability and high performance. Continuously monitor 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 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

Learn more about the LexisNexis Risk team and how we work

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