Research Scientist - NLP

Key Skills

Caffe, Computer Vision (CV), Deep Learning, Java Programming, Keras software library, Large data sets, Machine learning techniques, Natural Language Processing (NLP), Python Programming, PyTorch, TensorFlow, Torch library

Job Description

Natural Language Processing (NLP) is a frontier in Artificial Intelligence and Machine Learning. At Adobe Research, we are particularly interested in NLP for multimodal data, such as joint vision and language, video understanding with transcript, and document understanding. Advancing the state-of-the-art in this area is critical to Adobe’s mission of changing the world through the digital experience.

We are looking for a Research Scientist in NLP and Multimodal Learning to join a world-class Computer Vision, Deep Learning, and Natural Language Processing research lab at Adobe Research. You will initiate and execute research projects in NLP, Multimodal Learning, and related areas relevant to Adobe’s business. You will collaborate with researchers in Natural Language, Computer Vision, and Deep Learning on cross-disciplinary projects and partner with product teams to transfer research outcomes to Adobe products. You will have opportunities to mentor interns and work with our university collaboration program on state-of-the-art research topics interesting to Adobe and the academy. 

Required Qualifications

• PhD. in Computer Science or related field with research specialization in NLP, Machine Learning, or Computer Vision  
• Familiar with state-of-art deep learning frameworks, such as Tensorflow, PyTorch, Keras, Caffe, Torch. 
• Proficient in one or more programming languages such as Python, Java, and C/C++ 
• Excellent communication skills and intense teamwork experiences

Preferred Qualifications

• Strong publication record in NLP, Machine Learning, or Computer Vision  
• Experience in state-of-the-art NLP technologies (transformers, etc.)  
• Experience in multimodal machine learning (image+text, video+text, etc.)  
• Experience working with large-scale datasets  
• Track record of collaborating with researchers in adjacent domains such as Computer Vision, video, and document understanding  
• Experience in working with product teams on technology transfers