(222930) Software Engineer II (L3) - ML Plats Build & Train

Toronto, ON

Applications have closed

Wayfair Inc.

Shop Wayfair for A Zillion Things Home across all styles and budgets. 5,000 brands of furniture, lighting, cookware, and more. Free Shipping on most items.

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Who We Are

The Data and Machine Learning Platforms team paves the path for any Wayfair team to make informed decisions leveraging data and ML. This team builds and maintains multiple solutions for streaming data, analytics, ML model development and training, a feature store, centralized model registry, and a scalable model deployment platform.

 

What You’ll Do

  • Take complex engineering problems, design appropriate solutions and deliver on them fairly independently with limited oversight.
  • Work on a variety of technologies - from model deployment tools, to model monitoring using GCP, K8s and Python
  • Work closely as needed with the Data Science team and develop good architectural patterns allowing us to deploy ML models quickly and flexibly
  • Design systems that can handle large volumes of data and provide robustness, resilience to failures and smart anomaly detection capabilities
  • Be a multiplier, mentor other engineers on the team and help them become more productive and implement engineering best practices
  • Work with Senior Leadership to provide your vision and expertise to drive future products, and new features on existing products

What You’ll Need

  • 5+ years experience as a full stack, full lifecycle software engineer with a deep understanding of a modern programming languages
  • Experience working with Data Science teams and familiarity with Machine Learning concepts will be a big plus
  • Strong verbal and written communication skills
  • Ability to work effectively with engineers, product managers, and business stakeholders alike
  • Experience mentoring engineers and leading code and design reviews
  • Proficiency in designing robust, reliable systems at scale
  • Experience with data engineering at scale

 

About Wayfair Inc.

Wayfair is one of the world’s largest online destinations for the home. Whether you work in our global headquarters in Boston or Berlin, or in our warehouses or offices throughout the world, we’re reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If you’re looking for rapid growth, constant learning, and dynamic challenges, then you’ll find that amazing career opportunities are knocking.

No matter who you are, Wayfair is a place you can call home. We’re a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair – and world – for all. Every voice, every perspective matters. That’s why we’re proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or genetic information.

If you are you having any difficulty submitting your application, please reach out to our careers team at careers@wayfair.com.

We are interested in retaining your data for a period of 12 months to consider you for suitable positions within Wayfair. Your personal data is processed in accordance with our Candidate Privacy Notice (which can found here: https://www.wayfair.com/careers/privacy). If you have any questions regarding our processing of your personal data, please contact us at dataprotectionofficer@wayfair.com. If you would rather not have us retain your data please contact us anytime at dataprotectionofficer@wayfair.com. 

Tags: Engineering GCP Machine Learning ML models Model deployment Privacy Python Streaming

Perks/benefits: Career development

Region: North America
Country: Canada
Job stats:  2  0  0

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