Senior Applied Scientist, Computer Vision, Camera and Sensors
Job ID: 2923125 | Evi Technologies Limited
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 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 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.
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build.
Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information.
#J-18808-Ljbffr
