22 Jul 2026

Software Engineer

RELX

St Leonards

22 Jul 2026

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Software Engineer

LexisNexis Risk Solutions is seeking a Senior Software Engineer in St Leonards, New South Wales, Australia to develop advanced liveness detection systems using machine learning and deep learning to prevent spoofing attacks during biometric authentication. The role requires expertise in ML frameworks, programming, and anti-spoofing standards, with a focus on building world-class identity fraud prevention technology.

Core AIOn-siteFull-timeSeniorTensorFlowKeras

Software Engineer

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Core AIOn-siteFull-timeSeniorTensorFlow

Salary

Not specified

Work Location

St Leonards, New South Wales, Australia, AU

Work Model

On-site

Employment Type

Full-time

Experience Level

Senior

Core Qualifications

Technical (Must-have)

TensorFlowKerasPyTorchPythonJavaRMachine LearningDeep LearningStatisticsProbability TheoryData AnalysisNIST ISO/IEC 30107FIDO

Soft Skills

Problem-solvingCollaborationInnovative mindsetContinuous learning

Key Responsibilities

•Develop and design liveness detection systems that utilize AI algorithms to differentiate between real and fake biometric data, including analyzing facial features, eye movements, and other physiological indicators.
•Build and optimize deep learning models specifically for liveness detection, including selecting appropriate algorithms, conducting experiments, and optimizing model parameters to enhance accuracy and reliability.
•Identify and extract features from biometric data crucial for detecting spoofing attempts, including texture analysis, motion-based detection, and 3D depth analysis.
•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.
•Implement machine learning algorithms capable of processing real-time biometric data to detect inconsistencies indicative of spoofing attempts, including integrating multimodal approaches such as facial recognition, fingerprint scanning, and iris recognition.
•Conduct rigorous testing of liveness detection systems to ensure performance in real-world scenarios, validating models against various spoofing techniques to ensure robustness.
•Deploy liveness detection systems into production environments, ensuring scalability and high performance, and continuously monitor system outputs to identify any issues with accuracy or efficiency.

Software EngineerSeniorMachine LearningDeep LearningBiometric SecurityAnti-SpoofingLiveness DetectionTechnologyFull-timeOn-site

Key Responsibilities

•Develop and design liveness detection systems that utilize AI algorithms to differentiate between real and fake biometric data, including analyzing facial features, eye movements, and other physiological indicators.

•Build and optimize deep learning models specifically for liveness detection, including selecting appropriate algorithms, conducting experiments, and optimizing model parameters to enhance accuracy and reliability.

•Identify and extract features from biometric data crucial for detecting spoofing attempts, including texture analysis, motion-based detection, and 3D depth analysis.

•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.

•Implement machine learning algorithms capable of processing real-time biometric data to detect inconsistencies indicative of spoofing attempts, including integrating multimodal approaches such as facial recognition, fingerprint scanning, and iris recognition.

•Conduct rigorous testing of liveness detection systems to ensure performance in real-world scenarios, validating models against various spoofing techniques to ensure robustness.

•Deploy liveness detection systems into production environments, ensuring scalability and high performance, and continuously monitor system outputs to identify any issues with accuracy or efficiency.