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Applied Scientist, Computer Vision, Camera and Sensors, Cambridge
Client: Evi Technologies Limited
Location: Cambridge, United Kingdom
Job Category: Other
EU work permit required: Yes
Job Reference: 3071f0941001
Job Views: 4
Posted: 14.03.2025
Expiry Date: 28.04.2025
Job 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 job 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
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, an Applied Scientist 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 principal 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 application
* Experience in applied research
PREFERRED QUALIFICATIONS
* 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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