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Applied Scientist, Fashion

Job ID: 1789745 | Amazon Development Center DEU

DESCRIPTION

If you get excited by the prospect of solving hard problems using Computer Vision and Machine Learning, enjoy working in a fast-paced environment with thought leaders in the CV space, and are passionate about launching algorithms for maximum customer impact, then we have the perfect role for you!

We are looking for an expert in computer vision with a focus on data-driven image synthesis using deep learning techniques such as GANs and VAEs to help Amazon transform pixels into personalized fashion images. Our team is developing cutting-edge technology to personalize and transform photos, partnering with many different teams across Amazon to apply a mix of workflows, image generation, computer vision, and machine learning in the fashion space.

As an Applied Scientist, you will work in a team with other scientists and engineers working on products and prototypes in the field of image synthesis and photo-realistic appearance of people and clothing to create scalable solutions to customer problems. You will play a critical role in ideation for the team and run live experiments, with opportunities to publish your work. We are building the next generation of fashion imagery, and we hope you'll join us!

This role is located in Tuebingen. Germany, but we are open to hiring also in Berlin.




BASIC QUALIFICATIONS

· PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
· hands-on experience developing and implementing deep learning or computer vision algorithms.
· Experience with modern ML/CV frameworks such as PyTorch, TensorFlow, etc...
· Strong communication and data presentation skills
· Strong problem solving abilities
· Experience with generative deep learning models applicable to the creation of synthetic images like GANs, VAEs and NF.
· Experience programming in Java, C++, Python or related language

PREFERRED QUALIFICATIONS

· PhD in machine learning, computer vision, computer science or related field is preferred but relevant industry experience will be taken into account.
· Publications in top-tier venues (CVPR, ICML, NIPS, ICCV, ECCV, SIGGRAPH, etc.)
· Experience with generative deep learning models applicable to the creation of synthetic images like CNNs, GANs, VAEs and NF.
· Experience with machine learning techniques for fast and accurate extraction of visual features of humans (i.e. shape, pose, segmentation) from photographs. Hands on experience in this area is a strong plus.
· Experience with gradient descent and other forms of first and second order derivative-based optimization
· Experience with probabilistic models and statistical learning
· Experience with 3D graphics and/or geometric reconstruction
· Familiarity with cloud computing services such as AWS
Amazon Science (www.amazon.science) gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.


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