Who we are:
The Search and Recommendations ML team is responsible for the algorithms that power Wayfair's global search experience across all countries and stores as well as all other recommendation services at Wayfair (item-to-item, browse, email, etc.) for both our core e-shopping experience and brand-based content. Using state-of-the-art web-scale machine learning, including cutting-edge NLP, graph-based learning, and multi-modal technology, these teams power a fundamental set of experiences for our over 22 million active customers. Our mission is to help our customers determine their style and needs efficiently, delivering an end-to-end personalized and inspiring experience.

Hiring Leader : Patrick Phelps - https://www.linkedin.com/in/phphelps/

What You’ll Do:

• Take on technical leadership for the whole search and recs ML strategy for Wayfair both in the US and globally. 
• Provide technical leadership for Wayfair's search and recommendations ML strategy, both in the US and globally.
• Lead the development of cutting-edge multi-modal search and recommendation experiences designed to delight and engage our customers throughout their shopping journey, from inspiration to purchase and delivery.
• Develop a holistic strategy to evolve and power diverse product experiences using scalable and reusable cloud-based technology.
• Mentor and grow teams dedicated to delivering these at-scale experiences.
• Create a vision for and develop and improve the end-to-end shopping journey across all customer touchpoints.
• Design and implement at-scale ranking systems (retrieval, relevance, whole slate optimization) using a combination of web-scale customer behavioral data and our rich catalog of product information, directly powering substantial top and bottom-line growth.
• Promote a healthy ecosystem for all sides in the marketplace, from customers to suppliers, to promote sustainable growth and help overcome challenging marketplace problems: supply and demand matching, balancing diversity and exploration, and helping new products accelerate while overcoming cold-start problems.
• Develop extensible, reusable, and at-scale capabilities that can abstract across problem spaces.

What You’ll Need:

• 7+ years of industry experience in one or more of the following: Search, NLP, Ranking, Ads, Recommender systems, and Machine Learning.
• Strong technical skills: Advanced usage and hands-on ability with Python and/or Java for ML problems, experience with technical workflow serving tools, including all stages of batch and real-time workflows.
• Advanced statistical and quantitative knowledge and modeling techniques, including experimental design, statistical inference, hypothesis testing, and optimization.
• Experience managing large-scale ML projects, including roadmap creation, execution, and delivery.
• Ability to work with high-level business stakeholders, synthesize conclusions for non-experts, and influence business decisions at the Director+ level.
• Strong track record of publishing in world-leading ML forums (e.g., NeurIPS) is a plus.
• Experience leveraging cloud-native tech, GCP, and Vertex is a plus.
• Team management experience is a significant plus.

Assistance for Individuals with Disabilities

Wayfair is fully committed to providing equal opportunities for all individuals, including individuals with disabilities. As part of this commitment, Wayfair will make reasonable accommodations to the known physical or mental limitations of qualified individuals with disabilities, unless doing so would impose an undue hardship on business operations. If you require a reasonable accommodation to participate in the job application or interview process, please let us know by completing our Accomodations for Applicants form.

Need Assistance?

About Wayfair Inc.
Your personal data is processed in accordance with our Candidate Privacy Notice (https://www.wayfair.com/careers/privacy). If you have any questions or wish to exercise your rights under applicable privacy and data protection laws, please contact us at dataprotectionofficer@wayfair.com.