At a glanceSummarised by Seekless from the posting.
Must have5
Strong technical background in machine learning and deep learning
Developing novel models or algorithms and reporting results as published papers
Excellent analytical and programming skills for large-scale deep learning
Experience with research communities, including having published papers at conferences, for example NeurIPS, ICLR, ICML, CVPR, etc.
Strong communication and presentation skills
Nice to have2
Diverse experience and knowledge in generative models, representation learning or general realm of deep learning
Have some experience in multiple modalities of deep learning, such as computer vision, natural language processing or audio
Eligibility1
We will request at least one professional reference, including their contact information (e.g., email address), prior to the interview
Skills
machine learning
deep learning
computer vision
natural language processing
audio processing
Proposition summary
Sony AI’s Deep Generative Modeling (DGM) team delves into deep learning fundamentals and their practical applications for integration with Sony’s business. We are actively recruiting skilled research scientists or engineers with a robust engineering background to contribute to our endeavors. Joining us offers numerous opportunities to develop cutting-edge, large-scale AI models through internal collaborations. The technologies developed during the internship will have the potential to be applied in film, game, and music production across entertainment studios worldwide. This Tokyo-based position operates in an English-speaking environment.
Responsibilities
As a Research Intern, you will conduct novel and advanced research with internal members. You are expected to be self-motivated and have the ability to conduct and implement innovative ideas through internal collaborations. Our primary research interest include (but are not limited to):
1.
Efficient and/or scalable training/sampling of deep generative models
2.
Technologies for safe deep generative models, such as memorization mitigation/detection, concept erasing, and training data attribution
3.
Representation learning framework for multimodal generative models
we expect the outcome of your research will be published as academic papers.
Required Qualifications
•
Strong technical background in machine learning and deep learning
•
Developing novel models or algorithms and reporting results as published papers
•
Excellent analytical and programming skills for large-scale deep learning
•
Experience with research communities, including having published papers at conferences, for example NeurIPS, ICLR, ICML, CVPR, etc.
•
Strong communication and presentation skills
Preferred Qualifications
•
Diverse experience and knowledge in generative models, representation learning or general realm of deep learning
•
Have some experience in multiple modalities of deep learning, such as computer vision, natural language processing or audio
Important Note on Your Application
Please be aware that we will request at least one professional reference, including their contact information (e.g., email address), prior to the interview. References should be individuals you have worked with, preferably co-authors of your publications, and may include supervisors or academic collaborators.