Machine Learning Scientist III, Search

Wayfair LLC•Boston, MA

40d•Hybrid

About The Position

The Search and Recommendations Machine Learning (ML) team is at Wayfair is at the forefront of designing and implementing algorithms that define our global search experience. Using cutting-edge machine learning approaches-including deep sequence models, embeddings and multi-modal technologies-we aim to deliver a personalized and compelling experience for over 22 million active customers. Our mission is to make the user experience intuitive and efficient, helping customers discover exactly what they need in a vast and diverse product catalog. What You'll Do: Elevate recommendation quality: Design and implement scalable machine learning models to improve the ranking, and personalization of product recommendations across Wayfair Develop robust retrieval systems: Build and optimize candidate generation pipelines that surface high-quality, personalized product recommendations at scale. Leverage user and product signals: Apply deep learning and representation learning to model user preferences, product attributes, and contextual signals for better recommendation performance. Innovate with cutting-edge techniques: Explore sequence modeling, embeddings, and multi-modal modeling to drive the next generation of recommender systems. Collaborate cross-functionally: Partner with product managers, engineers, and data scientists to align recommendation strategies with business objectives and user needs. Tackle recommendation-specific challenges: Solve key issues such as the cold-start problem, data sparsity, product compatibility and seasonality in dynamic environments. Advance the ML community at Wayfair: Contribute to internal knowledge sharing, author technical documentation, and represent Wayfair at top ML conferences like NeurIPS and RecSys.

Requirements

Bachelor's or advanced degree (Master's, PhD) in Computer Science, Machine Learning, Mathematics, Statistics, or related field.
4+ years of industry experience as an ML engineer, applied scientist, or research scientist, with a proven track record of delivering ML projects autonomously and driving measurable business impact, particularly in recommendations, search, or ranking.
Expertise in recommendation systems, including candidate generation, ranking algorithms, and user-item modeling.
Deep understanding of collaborative filtering, sequence modeling, and embedding-based personalization.
Experience with end-to-end project ownership, including collaboration with business partners and strong written and verbal communication skills.
Strong proficiency in Python and/or Java for building and deploying ML-driven recommendation systems.
Experience deploying machine learning models in production environments, with a focus on cloud-based solutions such as GCP (BigQuery, GCS, Vertex AI, Composer), as well as workflow orchestration tools like Airflow, model tracking using MLflow, and containerization technologies like Docker.

Responsibilities

Elevate recommendation quality: Design and implement scalable machine learning models to improve the ranking, and personalization of product recommendations across Wayfair
Develop robust retrieval systems: Build and optimize candidate generation pipelines that surface high-quality, personalized product recommendations at scale.
Leverage user and product signals: Apply deep learning and representation learning to model user preferences, product attributes, and contextual signals for better recommendation performance.
Innovate with cutting-edge techniques: Explore sequence modeling, embeddings, and multi-modal modeling to drive the next generation of recommender systems.
Collaborate cross-functionally: Partner with product managers, engineers, and data scientists to align recommendation strategies with business objectives and user needs.
Tackle recommendation-specific challenges: Solve key issues such as the cold-start problem, data sparsity, product compatibility and seasonality in dynamic environments.
Advance the ML community at Wayfair: Contribute to internal knowledge sharing, author technical documentation, and represent Wayfair at top ML conferences like NeurIPS and RecSys.

Benefits

Paid Holidays
Paid Time Off (PTO)
Full Health Benefits (Medical, Dental, Vision, HSA/FSA)
Life Insurance
DIsability Protection (Short Term & Long Term DIsability)
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