Computer Vision - Applied Scientist

5 days agoPasadena, CA


Do you want to work on cutting edge research in computer vision, deep learning and machine learning to solve document understanding? Come join the world class researchers and academics in the AWS Computer Vision research team who are developing the science that powers Amazon Textract!

AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops.

Our research themes include, but are not limited to: unsupervised, self-supervised and semi-supervised methods, active learning and semi-automated data annotation, document OCR and scene text recognition, visual question answering (VQA), document VQA, NLP+vision, extracting tabular data from documents, document understanding, and layout understanding.

We are located in Seattle, Pasadena, Palo Alto, Atlanta (USA) and in Haifa and Tel Aviv (Israel).

Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.

Work/Life Balance
Our team puts a high value on work-life balance. It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.


• PhD degree with 4 years of applied research experience or a Masters degree and 6+ years of experience of applied research experience
• 3+ years of experience in building machine learning models for business application
• Experience programming in Java, C++, Python or related language


• Experience with OCR, scene text detection, extraction of structured data such as tables from documents, document understanding, VQA and document VQA models
• Experience with deep learning libraries such as PyTorch, TensorFlow, MxNet
• Experience with conducting research in a corporate setting
• Excellent publication record in peer reviewed conferences and journals
• Proven expertise in conducting independent research and building computer vision systems.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, visit

Client-provided location(s): Pasadena, CA, USA
Job ID: Amazon-1422984

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