Machine Learning Engineer
Machine Learning Engineer
Introduction to the team:
The members of Wayfair’s 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
Check out some of our work here: https://tech.wayfair.com/team-data-science/
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. You’ll work within Wayfair’s latest big data technology infrastructure to develop innovative and new machine learning engineering capabilities.
The Data Science department covers these main topic areas. You will work in one of the following:
Imagery and style is at the core of Wayfair’s catalog offering. At Computer Vision, we use the latest in the research community to build algorithmic intelligence of Wayfair’s millions of images for our customers, suppliers, and in-house scientists
Our algorithms dynamically price millions of products every day. We are constantly automating real-time experiments at scale and running complex statistical models to infer optimal prices via our understanding of customer and competitor behavior.
Wayfair invests hundreds of millions of dollars in annual marketing spend, and we optimize the return using attribution, segmentation, and forecasting.
We are building an algorithmic marketplace for our suppliers & customers. Using product imagery and text, we create meta-tagging that fits products within our catalog and we layer on additional models to understand how their style and how they should be curated.
- 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
- Work experience with implementing machine learning in a low latency real time web server platforms and/or highly scalable offline batch processes
- Intense intellectual curiosity – strong desire to always be learning
- Analytical, creative, and innovative approach to solving open-ended problems
- Highly collaborative, team-player attitude
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