Our team vision is simple yet complex: Create 3D models for every object sold on Amazon.
We apply a mix of workflows, image processing, computer vision and machine learning techniques.
We are seeking an Applied Scientist with a background in Machine Learning applied to Computer Vision or Computer Graphics. As part of a world-class research team, you will be working with an Amazon-scale dataset, with Amazon-scale computing resources to devise methods to reconstruct 3D objects from a set of sparse visual inputs.
Imaging Sciences offers a dynamic workplace that is fueled by innovation and passionate collaboration in a highly multidisciplinary team. We take pride in developing cutting-edge technologies and products that are optimized for the best customer experience. Amazon Imaging Science's vision is to provide the best product imagery in the industry to empower customers. Through technology, we seek to constantly increase the quality of photos, videos, and other visual media, to lower the cost of acquisition, and to create innovative imaging products.
To know more about Amazon science, Please visit https://www.amazon.scienceBASIC QUALIFICATIONS
- PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
- Experience programming in Java, C++, Python or related language
- Doctorate in Computer Science, Electrical Engineering, or related field
- Research background focusing on Neural rendering, computer vision, 3D reconstruction, and/or machine learning
- Able to get inspiration from literature reviews to imagine new ideas
- Track record of successfully collaborating with engineering on cutting-edge projects in a corporate environment
- Research experience in ML and Deep Learning for 2D and 3D content
- Proficiency in Python
- Experience working on content authoring and/or 3D systems
- Experience working within a product development team
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, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.