Machine Learning Manager - Recommendations
: Job Details :


Machine Learning Manager - Recommendations

Wayfair

Location: Boston,MA, USA

Date: 2024-12-11T07:40:33Z

Job Description:
About this role: We are looking for an experienced ML team manager to lead our product and content recommendation team focused on building intelligent ML-based recommender systems (e.g. item-2-item, home page, email and category pages) for Wayfair. You will own the core recommendation systems that power across all of our surfaces, delivering relevant and engaging content and product recommendations that unlock significant commercial value and contribute directly to Wayfair's bottom line. You will partner closely with backend engineers and data scientists to overcome some of Wayfair's most intellectually challenging machine learning, latency, and scalability problems. Wayfair's SMART (Search, Marketing, and Recommendations Technology) team is at the forefront of shaping how millions of customers discover and engage with products. We leverage cutting-edge machine learning, artificial intelligence, and data-driven strategies to deliver personalized shopping experiences. As a member of our SMART team, you'll be responsible for designing, implementing, and optimizing systems that enhance search capabilities, develop highly relevant product recommendations, and drive innovative SOTA solutions. What you'll do:
  • Lead our Recommendations team within the Search and Recs Machine Learning group responsible for building and maintaining systems that power recommendations across all surfaces on our site, our app, email, and push and drive substantive business value.
  • Hire, develop, and coach a talented team of ML scientists to build scalable ML decisioning systems that directly contribute to Wayfair's bottom-line
  • Partner closely with cross-functional partners across engineering, data science and product to develop science strategy and roadmap for recommendations systems
  • Design, build, deploy and refine extensible, reusable, large-scale, and real-world platforms that improve customer experience
  • Build robust monitoring, alerting, and edge-case handling mechanisms.
  • Collaborate closely across multiple science and engineering teams to develop SOTA recommendation technologies and drive robust integration to launch improving customer experiences.
  • Research new developments in sort and recommendations research and open-source packages, and incorporate them into our internal packages and systems.
Who you are:
  • 6+ years of experience (ideally with 2+ YOE as lead/manager) building advanced machine learning models that solve real-world problems
  • Strong theoretical grasp of machine learning concepts combined with hands-on expertise deploying web-scale ML-based decision-making systems into production
  • Hands-on and technical manager who can engage deeply with both core algorithm development and system design & architecture
  • Experience with data-driven opportunity sizing & prioritization and bias towards building things iteratively (and learning as we go)
  • You are comfortable making complex decisions (even when faced with ambiguity), making pragmatic tradeoffs, and using goal-setting frameworks (e.g. OKRs)
  • You have a track record of coaching and mentoring junior ML scientist and engineersranging from fresh PhD graduates to experience ML scientist
  • Experience working with commercial stakeholders to translate business objectives to appropriately-scoped ML model/system and ensuring commercial and ML objectives remain tightly aligned
  • Strong written & verbal communication skills and ability to influence senior-level stakeholders and steer overall strategy based on data-driven recommendations and analysis
  • Familiarity with ML model development frameworks, ML orchestration and pipelines with experience in either Airflow, Kubeflow or MLFlow as well as Spark, Kubernetes, Docker, Python, and SQL.
  • Nice to have:
    • Experience building core recommendations systems for eCommerce and/or other 2-sided marketplaces
    • Experience with online learning, RL, or ML-based control systems
Why You'll Love Wayfair:
  • Time Off:
    • Paid Holidays
    • Paid Time Off (PTO)
  • Health & Wellness:
    • Full Health Benefits (Medical, Dental, Vision, HSA/FSA)
    • Life Insurance
    • Disability Protection (Short Term & Long Term Disability)
    • Global Wellbeing: Gym/Fitness discounts (including US Peloton, Global ClassPass, and various regional gym memberships)
    • Mental Health Support (Global Mental Health, Global Wayhealthy Recordings)
    • Caregiver Services
  • Financial Growth & Security:
    • 401K Matching (Employee Matching Program)
    • Tuition Reimbursement
    • Financial Health Education (Knowledge of Financial Education - KOFE)
    • Tax Advantaged Accounts
  • Family Support:
    • Family Planning Support
    • Parental Leave
    • Global Surrogacy & Adoption Policy
  • Professional Development & Recognition:
    • Rewards & Recognition
    • Global Employee Anniversary Awards
    • Paid Volunteer Work
  • Unique Perks:
    • Employee Discount
    • U.S. Bluebikes Membership
    • Global Pod Outings
  • Work/Life Balance:
    • Emphasizing a supportive & flexible work environment that encourages a balance between personal and professional commitments
Massachusetts Applicants: I understand that it is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. 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, genetic information, or any other legally protected characteristic. Your personal data is processed in accordance with our Candidate Privacy Notice ( If you have any questions or wish to exercise your rights under applicable privacy and data protection laws, please contact us at ...@wayfair.com.
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