Software Development Engineer Amazon
New York, NY

Job Description

Help us turn pixels into people.

Join our team of world class computer vision researchers and ML-focused software engineers as we continue to develop the world's most accurate, data-driven 3D models of human pose, shape and motion. Our team at Amazon is an outgrowth of Body Labs, an NYC-based computer vision startup which Amazon acquired at the end of 2017.

First at Body Labs, and now Amazon, our team has been developing state-of-the art computer vision algorithms for accurately inferring the 3D shape and pose of people in everyday images and video. Our technology builds on over a decade of computer vision research, licensed in part from Prof. Michael Black's research group at Brown University and the Max Planck Institute for Intelligent Systems.

As part of our team, you will help us leverage high quality 3D and 4D data in order to create highly accurate statistical 3D models of the human body.

You will be a part of the engineering team that helps our scientists develop and implement deep learning algorithms and other forms of optimization in order to fit these 3D models to images and videos of people. As part of the engineering group, you will help us pursue a wide range of customer facing applications for our body model technologies. You will help us extend and refine these technologies to meet needs of Amazon customers.

As an SDE working at Body Labs, you will be part of a team that is responsible for the design and implementation of new software initiatives, built from the ground up with a wealth of Amazon infrastructure and services. You will work closely with ML/CV scientists to develop new algorithms, libraries, and infrastructures and deliver them into Amazon's broader ecosystem as well as externalize them through AWS.

We are looking for candidates who can deal with the planning ambiguity we get from never being 100% sure the research is going to pan out as expected.

Amazon.com is an Equal Opportunity-Affirmative Action Employer - Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation