Senior Applied Scientist, Amazon Go

AWS Applications and Higher Level Abstractions (Apps) provides horizontal and industry vertical applications for business users with the same on-demand scalability, reliability, pay-as-you-go pricing, and machine learning expertise that drive AWS services. The AWS Applications group includes services such as Amazon Connect (a cost-effective cloud contact center), our End User Computing (including Amazon Workspaces, AppStream, etc.), Marketing Tech (Amazon Pinpoint), and Autonomous Checkout and Biometric Identity Services (Just Walk Out, Amazon One) for retail, sports, travel, and other verticals.

The Role: Everyone on the team needs to be entrepreneurial, wear many hats and work in a highly collaborative environment that's more startup than big company. We'll need to tackle problems that span a variety of domains: computer vision, image recognition, machine learning, real-time and distributed systems.

As an Applied Scientist, you will help solve a variety of technical challenges and mentor other engineers. You will tackle challenging, novel situations every day and given the size of this initiative, you'll have the opportunity to work with multiple technical teams at Amazon in different locations. You should be comfortable with a degree of ambiguity that's higher than most projects and relish the idea of solving problems that, frankly, haven't been solved at scale before - anywhere. Along the way, we guarantee that you'll learn a ton, have fun and make a positive impact on millions of people.

BASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.

Posted: September 4, 2024 (Updated 19 days ago)

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