Associate Director, Product Management, Machine Learning

Boston, MA

Full Time Mid-level / Intermediate
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Wayfair Inc.
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Wayfair customer’s experience is increasingly driven by a cutting-edge set of machine learning systems that interact in complex ways to ensure that we are using our rich datasets to their full potential. Business applications of these learning systems span many fields including recommendations, marketing, supply chain optimization and merchandising. These fields require a sophisticated technology stack that allows for complex machine learning models combined with configurability for rapid testing and exploration. 

We are looking for a seasoned Product Manager to join our Machine Learning Platforms team that is building Wayfair’s cutting edge platforms that will enable us to deliver world class ML solutions that are helping serve our customers across their journey with Wayfair. The work includes but is not limited to the intricacies involved in developing scalable platform capabilities for feature management, model training and deploying models across a range of business functions. In a nutshell these platforms power the model development lifecycle and cater to the diverse use cases across our global community of hundreds of data scientists. 

We’re looking for someone who not only enjoys creating a bold vision but also executing on their ideas through fruition on a global scale. In this role, you will be owning a range of products that will offer cloud native capabilities to ensure our Data Scientists can focus on model development and delivering cutting edge intelligent solutions. Your goal will be to empower any team across the company with self-service software to deploy, manage, and integrate models with their systems without the need for specialized ML knowledge.

You will work with a variety of stakeholders and partners in both engineering and data science. You will work with them to understand their pain points, our internal business KPIs, and develop a deep understanding of the current technical gaps and how to bridge them with a set of capabilities that advance our time to insight velocity. You’ll develop a bold vision, an actionable roadmap, translate business asks into sensible technical specifications for your engineering team, making smart trade-offs between time and complexity to develop MVPs.  You’ll serve as the subject matter expert on the platform, push for adoption for new use cases, and continually expand our machine learning capabilities.


  • Own the strategy and implementation of your products
  • Leverage your deep knowledge of distributed systems engineering to build Wayfair’s next generation Machine Learning capabilities
  • Think outside of the current technology/stack limitations to push the boundaries on what is possible and deliver feasible solutions collaboratively
  • Champion open source solutions and Google Cloud native technologies, and their application to our use cases
  • Be the subject matter expert of Wayfair’s ML capabilities and how your products will advance them
  • Prioritize many requests and ideas for features by understanding the business value and impact, weighed against the risks and development cost
  • Maintain a product vision and roadmap, keeping stakeholders and constituents up to date on the top level goals and timelines
  • Market your product internally to various departments to ensure all available users know about your product and how they could value from it
  • Translate business initiatives into engineering stories/tickets, allowing engineering to run with your ideas
  • Have an in-depth understanding of the technology used in your products, the strong and weak points, and become an expert at what is available
  • Measure success and inform pivots through well planned and instrumented analytics
  • Regularly communicate our quarterly/monthly goals and progress to keep business stakeholders apprised of your work and product progress


  • 7+ years of product experience in developing data-driven products that are cloud native 
  • Good understanding of ML lifecycles and experience developing ML-driven products
  • Strong written and verbal communication and a demonstrated ability to explain technical concepts to non-technical audiences
  • Demonstrable ability to be technically hands-on, up to architecting high-level system plans (no coding)
  • Understanding of big data technologies, data lakes, streaming / real-time data solutions
  • Understanding of ML Infrastructure and scaling it on public cloud platforms
  • Ability to work across several stakeholder groups and juggle many large initiatives simultaneously
  • Ability to structure problems, develop clear hypotheses, and prioritize work against the largest impact initiatives
  • Experience working with a large engineering team, running their sprints, stand-ups, and backlog
  • Cultivate senior presence and be the leader of your portfolio of products

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.

Job region(s): North America
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