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. This involves selecting appropriate algorithms, conducting experiments, and optimizing model parameters to enhance accuracy and reliability.
Identify and extract features from biometric data that are 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. Ensure 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 which includes 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. Validate models against various spoofing techniques to ensure robustness.
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

Bachelor’s degree in computer science, Mathematics, or a related field.
In-depth understanding of machine learning frameworks such as TensorFlow, Keras, or PyTorch.
Experience in developing deep learning models is essential.
Proficiency in programming languages such as Python, Java, or R for model development and algorithm implementation.
Problem-solving abilities with a solid grasp of statistics, probability theory, and data analysis techniques.
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, 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.

Benefits

Medical Inpatient and Outpatient Insurance: Coverage for your healthcare needs.
Life Assurance Policies: Providing financial security for your loved ones.
Modern Family Benefits: Support for maternity, paternity, and adoption needs.
Long Service Award: Recognition for your dedication and loyalty.
Celebratory Allowance/Gifts: Marking special occasions to celebrate with you.
Flexible Benefits Plan : Offering you wider choice of services and products
Employee Assistance Program : Access support for personal and work-related challenges.
Flexible Working Arrangements: Balance work and personal life effectively.
Access to Learning and Development Resources: Empowering your professional growth.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

liveness detectionAI algorithmsdeep learning modelsmachine learning algorithmsfeature extractiontexture analysismotion-based detection3D depth analysisprogramming languagesdata analysis techniques

Soft Skills

problem-solvingcollaborationcross-functional teamworkinnovative mindsetcontinuous learning