Senior Liveness Detection Engineer
Develop advanced systems to prevent spoofing attacks during biometric authentication.
Our team seeks a skilled Senior Liveness Detection Engineer with expertise in designing and implementing AI-driven solutions for real-time liveness detection. The ideal candidate will have hands-on experience with machine learning frameworks, including TensorFlow, Keras, or PyTorch, and a strong understanding of deep learning models.
The successful applicant will be responsible for developing and optimizing liveness detection systems that utilize AI algorithms to differentiate between real and fake biometric data. This includes building deep learning models specifically for liveness detection, selecting appropriate algorithms, conducting experiments, and optimizing model parameters to enhance accuracy and reliability.
Key Responsibilities:
* Design and implement AI-driven liveness detection systems utilizing machine learning frameworks.
* Build and optimize deep learning models for liveness detection, ensuring high accuracy and reliability.
* Collaborate with cross-functional teams to integrate multimodal approaches such as facial recognition, fingerprint scanning, and iris recognition into the liveness detection system.
* Conduct rigorous testing of liveness detection systems to ensure performance in real-world scenarios.
Requirements:
* Machine Learning Expertise: In-depth understanding of machine learning frameworks such as TensorFlow, Keras, or PyTorch.
* Programming Skills: Proficiency in programming languages such as Python, Java, or R.
* 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 to achieve common goals.
* Experience in similar roles focusing on anti-spoofing or biometric security systems.