Wayfair - Seattle, WA

posted 4 months ago

Full-time - Mid Level
Seattle, WA
Furniture, Home Furnishings, Electronics, and Appliance Retailers

About the position

Wayfair is seeking an experienced Senior Machine Learning Scientist to join our Supplier Advertising ML Science team. This role is pivotal in the development of our smart bidding platform, which includes features such as tROAS, targeting enhancements, smart campaigns, and bid recommendations. As part of a cross-functional team, you will leverage your expertise in machine learning and engineering to tackle some of the most impactful challenges in our advertising business. You will collaborate closely with other scientists, product managers, and engineers to create and refine machine learning capabilities that enhance our advertising systems and improve customer experience. In this position, you will provide technical leadership in developing an automated and intelligent advertising system. Your responsibilities will include advancing state-of-the-art machine learning techniques to support bidding and optimizations, designing and deploying large-scale platforms, and building robust monitoring and alerting mechanisms. You will also be expected to research new developments in advertising and recommendations, integrating relevant findings into our internal systems. This role requires a strong understanding of business problems and the ability to develop appropriately scoped machine learning solutions in collaboration with various stakeholders. Wayfair values a culture of machine learning excellence, and you will be encouraged to participate in weekly research and development sharing sessions to promote this culture within the team. This position is based in Seattle, WA, and candidates are expected to comply with the team's hybrid work schedule requirements.

Responsibilities

  • Provide technical leadership in the development of an automated and intelligent advertising system.
  • Advance the state-of-the-art in machine learning techniques to support bidding and other optimizations.
  • Design, build, deploy, and refine extensible, reusable, large-scale, and real-world platforms that optimize our ads experience.
  • Build robust monitoring, alerting, and edge-case handling mechanisms.
  • Collaborate closely with Ads and Search & Recommendations Product and Engineering partners to integrate the smart bidding platform with existing infrastructure.
  • Research new developments in advertising and recommendations, incorporating them into internal packages and systems.
  • Work cross-functionally with commercial stakeholders, engineers, analysts, and product managers to understand business problems and develop ML solutions.
  • Promote a culture of machine learning and ML science excellence by participating in weekly research, learning, and development sharing sessions.

Requirements

  • Advanced degree (Master or PhD) in Machine Learning, Computer Science, Engineering, Statistics, or a related quantitative field.
  • 3+ years (with PhD) or 5+ years (non-PhD) of experience in advanced machine learning and statistical modeling, including hands-on designing and building production models at scale.
  • Strong theoretical understanding and solid hands-on expertise deploying ML-based decision-making systems into production.
  • 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-haves

  • Experience in computational advertising, bidding algorithms, or search ranking.
  • Familiarity with Machine Learning platforms offered by Google Cloud and how to implement them on a large scale (e.g. BigQuery, GCS, Dataproc, AI Notebooks).

Benefits

  • Paid Holidays
  • Paid Time Off (PTO)
  • Full Health Benefits (Medical, Dental, Vision, HSA/FSA)
  • Life Insurance
  • Disability Protection (Short Term & Long Term)
  • Gym/Fitness discounts (including US Peloton, Global ClassPass, and various regional gym memberships)
  • Mental Health Support (Global Mental Health, Global Wayhealthy Recordings)
  • Caregiver Services
  • 401K Matching (Employee Matching Program)
  • Tuition Reimbursement
  • Financial Health Education (Knowledge of Financial Education - KOFE)
  • Tax Advantaged Accounts
  • Family Planning Support
  • Parental Leave
  • Global Surrogacy & Adoption Policy
  • Rewards & Recognition
  • Global Employee Anniversary Awards
  • Paid Volunteer Work
  • Employee Discount
  • U.S. Bluebikes Membership
  • Global Pod Outings
  • Supportive & flexible work environment that encourages a balance between personal and professional commitments
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