Intern Research Intern

Sony AI is seeking research interns to join our Privacy-Preserving Machine Learning (PPML) team. Our team mainly focuses on fundamental and applied research, with a focus on building vision foundation models in a responsible manner. The role of a research intern is to conduct innovative research, develop methodologies, design and prototype solutions. You will work with a fast-growing team of world-class scientists and engineers to tackle the most challenging problems in foundation models and generative AI, including vision foundation model (VFM), knowledge transfer into VFM, data synthesis, federated learning, and model compression from VFM to small models on edge. You will see your ideas not only published in papers, but also improve the experience of millions of users of Sony. 

Roles and Responsibilities: 

• Conduct fundamental and innovative research in large vision foundation model, data synthesis, federated learning and knowledge distillation, including but not limited to architecture design and methodology design. 

• Be self-motivated and capable of proposing and implementing innovative ideas. 

• Deep understanding of large vision foundation model development and various CV applications, such as Image classification, object detection, pose detection, semantic image segmentation, etc. 

• Write reports and give presentations to internal and external audiences. 

• Contribute to library and tool development to support research and business. 

• Publish influential research outcomes in top-tier conferences and journals. 

Required Qualifications and Skills: 

• Currently has, or is in the process of obtaining, a master/PhD degree in computer science or related field. 

• Publications or expertise in computer vision applications (e.g., object detection, segmentation), vision and multi-modal foundation model, data synthesis, knowledge distillation, federated learning, etc. 

• Ability to communicate research in a clear and precise manner. 

• Excellent analytical and programming skills in large-scale deep learning.  

• Familiar with Python, Pytorch, etc. 

• Experience with research communities, including having published papers at conferences, e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, etc. 

• Strong communication and presentation skills