Job Post

Computer Vision Machine Learning Engineer PhD

4 Copley Place - Floor 7
Boston, MA 02116

Introduction to the team:

The members of Wayfairs Data Science group come from a range of highly quantitative backgrounds (think astrophysics, economics, cognitive science, and operations research, engineering and math).

The projects that our teams work on are driven from the ground up we look for entrepreneurial individuals that want to take ownership over their own agenda and thrive in a collaborative team environment.

Our Computer Vision team uses the latest in the research community to build algorithmic intelligence of Wayfairs millions of images for our customers, suppliers, and in-house scientists. Imagery and style is at the core of Wayfairs catalog offering.

Check out some of our work here:

Many of our projects are new and mostly projects that have never been worked on before. The work we do encompasses:

  • Modular algorithm design develop re-usable building blocks for quantitative models, leveraging high parallel, distributed machine learning and advanced data analysis techniques
  • Algorithm platform engineering architect, build, and maintain technical platforms for our algorithmic engines to run at scale, both for online and offline needs
  • Influencing business decisions relentlessly leverage our work and encourage adoption across our business partners, to drive real business value
  • Data mining work together with data scientists to uncover deep insight hidden in our vast repository of raw data, and provide tactical guidance on how to act on findings

As part of this role, you will use your software engineering skills to help build scalable machine learning models that drive value across multiple areas of the business. Youll work within Wayfairs latest big data technology infrastructure to develop innovative and new machine learning engineering capabilities.


  • Currently enrolled in a PhD program at a top-tier institution with a strong academic track record.
  • 2+ years of software engineering experience or advanced degree in quantitative field w/ material exposure to coding (e.g. mathematics, economics, computer science, physics, neuroscience, operations research etc.)
  • Intuitive sense of how to architect high performance distributed computing systems for machine learning & tie them to business problems
  • Strong background in machine learning and parallel processing pipelines
  • High comfort level with programming, e.g. languages such as Python, R, Scala, etc
  • Intense intellectual curiosity strong desire to always be learning
  • Analytical, creative, and innovative approach to solving open-ended problems
  • Highly collaborative, team-player attitude
Category: Data Science / Machine Learning

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