Machine Learning Manager - Advertising Science

About This Role We are looking for an experienced ML manager to lead a team focused on building intelligent ML-based bidding systems (e.g., tROAS, dynamic bidding, smart campaigns) for Wayfair’s sponsored products advertising business. You will have the opportunity to build 0-to-1 capabilities that unlock significant commercial value and contribute directly to Wayfair’s bottom line. You will partner closely with very talented engineers and scientists to overcome some of Wayfair’s most intellectually challenging machine learning, latency, and scalability problems. Wayfair's Customer Technology organization 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 organization, you'll be part of a team designing, implementing, and optimizing systems that optimize advertising goals, enhance search capabilities, develop highly relevant product recommendations, and drive innovative marketing solutions. What You’ll Do Lead our Intelligent Bidding pod within the Advertising Science Machine Learning group responsible for building 0-to-1 intelligent bidding capabilities (e.g. target ROAS, dynamic bidding, etc.) for Wayfair’s advertising platform. 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, science, analytics and product to develop science strategy and roadmap for Supplier Ads bidding systems. Design, build, deploy and refine extensible, reusable, large‑scale, and real‑world platforms that improve supplier experience, ROAS, and spend on Wayfair’s Sponsored Products. Build robust monitoring, alerting, and edge‑case handling mechanisms. Collaborate closely across multiple science and engineering teams to drive robust integration of our smart bidding platform with the existing infrastructure & systems. Research new developments in advertising, sort and recommendation research and open‑source packages, and incorporate them into our internal packages & 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 scientists and engineers — ranging from fresh PhD graduates to experienced ML scientists. 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 & 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 intelligent bidding and/or advertising systems (e.g. CPC bidding, tROAS, etc.) for eCommerce and/or other 2‑sided marketplaces. Experience with online learning, RL, or ML‑based control systems. Benefits 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 Workplace Expectations All Seattle‑based corporate employees will be in office in a hybrid capacity. Employees will work in the office on designated days Tuesday, Wednesday, and Thursday, and work remotely Monday and Friday. This role is also open to sit in Boston, MA. Accessibility 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 Accommodations for Applicants form. Additional Information For more information about applying for a career at Wayfair, visit our FAQ page here. 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 View email address on click.appcast.io. #J-18808-Ljbffr Wayfair