We are looking for a Research Intern.
Research Intern in the challenging areas of multimodal foundation models with application to a wide variety of business use-cases such as multimodal alignment, question answering, and information extraction. The research will also include concrete tasks such as document understanding, layout analysis, text extraction, image understanding, and data synthesis.
Role and Responsibilities :
If youre a student interested in the fields of machine learning, deep learning, and computer vision, and youre looking to come to a summer intern position where you will do research with academic and industrial impact, then this position is for you!
Our team develops technologies, models, algorithms, and software that make an impact on our products and on the world, and we publish papers and issue patents based on the work we do.
This internship involves solving a real-world problems using cutting edge deep learning/machine learning methods, with the aim to advance the state of the art in the domain of document understanding. Document understanding is the ability to read documents, understand their structure and content and act upon it. This is a crucial technology as business documents are key to the day-to-day operation of organizations.
Document understanding remains a research challenge that requires a multi-disciplinary perspective, spanning textual analysis, visual comprehension, layout understanding, knowledge representation, data mining and more. The areas we are looking at include also multimodal and foundation models, image understanding, and data synthesis.
To achieve the internship goal, you will collaborate with fellow team members and have access to nearly limitless compute power (GPU). The research topics for this internship include, novel self-supervised learning techniques, realistic data synthesis, Vision and Language multimodal research, and more.
The results of the project aim to include a publication in a top AI conference and development of a prototype demonstrating new AI functionality.
Succeeding in these tasks is expected to make an important impact on the research community in these exciting fields and lead to strong publications in a leading CV venue (e.g. CVPR / ICLR / ICCV).
Requirements: M.Sc. or Ph.D. student with knowledge in Machine Learning, Computer Vision, and Deep Learning
Strong CV background using modern methods, deep knowledge of the recent literature, prior CV/ML/DL publications is an advantage
Strong python coding skills. Experience with PyTorch or TensorFlow is an advantage
A team player with great social skills, willingness to collaborate
Strong background in Deep Learning methods. Knowledge of the recent literature and being able to discuss architectural concepts advantage.
This position is open to all candidates.