Deep Learning

1 week ago


Singapore VIDA Digital Identity Full time

Our mission is to create innovative, robust, and user-friendly digital identity solutions. We are looking for a passionate and skilled Deep Learning AI Scientist specializing in Liveness Detection and Biometrics to join our dynamic team. Your work will directly impact the security and reliability of VIDA's identity verification systems.

Responsibilities:

  • Liveness Detection Development: Design, train, and deploy advanced deep learning models to ensure robust liveness detection, preventing spoofing attacks using photos, videos, masks, or other methods.
  • Design, train and deploy biometric models to correctly identify users.
  • Own the full lifecycle of deploying models: from data labelling, working with engineers to design scalable APIs, to monitoring and A/B testing new model versions.
  • Stay updated with the latest research in biometrics, computer vision, and deep learning, incorporating new techniques to improve VIDA’s products.
  • Collaborate with business, product, operations and engineering teams to deliver impact for our customers.
  • Work independently or in a team to solve complex problem statements.

Requirements:

  • An advanced degree in a quantitative field, and 3+ years of hands-on experience in deep learning model development for biometrics or liveness detection or a similar field.
  • Deep understanding of modern computer vision techniques, deep learning and machine learning.
  • Experience developing and deploying machine learning models in production.
  • Experience with adversarial training to enhance model robustness.
  • Proficient in Python, C++, Scala, or Java.
  • Familiarity with modern deep learning frameworks such as TensorFlow, PyTorch, MXNet.
  • Familiarity with cloud platforms like AWS, GCP, or Azure for model deployment.
  • Experience in on-device inference for machine learning models is a plus.
  • Take pride in taking ownership and driving projects to have business impact.
  • Thrive in a fast moving collaborative environment.
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