Senior Applied Scientist, Computer Vision, Camera and Sensors

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Senior Applied Scientist, Computer Vision, Camera and Sensors

Sector: Media and Publishing, Science and Pharmaceutical, Technology
Role: Senior Executive
Contract Type: Permanent
Hours: Full Time

DESCRIPTION
The Camera and Sensors team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to help build industry-leading technology with computer vision and multimodal perception models for various Amazon devices.

Key Responsibilities
As an Applied Scientist with the Camera and Sensors team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with multimodal models with an emphasis on computer vision. Your work will directly impact our customers in the form of products and services that make use of Computer Vision technology. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances for Amazon devices.

A Day in the Life
As an Applied Scientist with the Camera and Sensors team, you will support the science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, you will also work closely with talented engineers and scientists to put algorithms and models into practice.

About the Team
You will work with a team of applied scientists and software engineers locally in Cambridge, along with a broader team of principle scientists, applied scientists, and software engineers across multiple global teams in the devices group.

BASIC QUALIFICATIONS

• PhD
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning
• Experience in building machine learning models for business applications
• Experience in applied research

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, etc.
• Experience in implementing Computer Vision algorithms

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