Research Intern (Privacy-Preserving Machine Learning)

Machine Learning, Computer Vision


Location flexible (Tokyo, Zurich, US)

General Information

Sony AI is seeking research interns to join our Privacy-Preserving Machine Learning (PPML) team. Our team focuses on fundamental and applied research in CV privacy. Our research interns have an opportunity to conduct innovative research and apply their novel ideas to real-world AI applications (e.g., Imaging&Sensing) in Sony. This internship requires a minimum of 3-month duration. The ideal candidate should have an enthusiasm for breakthroughs in secure and privacy-preserving machine learning.

Roles and Responsibilities

  • Conduct fundamental and innovative research in privacy and security related areas, including but not limited to data anonymization, differential privacy, adversarial training, machine unlearning, homomorphic encryption, federated learning, secure multi-party computation, training/inference on encrypted data, etc.
  • Identify new privacy-preserving and robust machine learning approaches in various CV applications, such as Image classification, object detection, pose detection, semantic image segmentation, etc.
  • Participant in security and privacy related projects to empower real-world AI applications in Sony, specifically Imaging&Sensing business.
  • Contribute to library and tool development to support research and business.
  • Write reports and give presentations for internal audiences.
  • Publish influential research outcomes in top-tier conferences and journals.

Required Qualifications and Skills

  • Currently has, or in the process of obtaining, a PhD degree in computer science or related field.
  • Publications or expertise in privacy and security, computer vision, tiny-device learning, adversarial learning, distributed/decentralized system design, communication efficiency, etc.
  • Ability to communicate research in a clear and precise manner.
  • Familiar with Python, C++, Pytorch, Tensorflow, etc.

Working Location

Location flexible (Tokyo, Zurich, US)

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