Machine Learning II

Who we are

Wayfair is moving the world so that anyone can live in a home they love – a journey enabled by more than 3,000 Wayfair engineers and a data-centric culture. The Customer Technology(CT) team builds and owns all the Machine learning (ML) products that power all search, marketing, and recommendations technology across Wayfair. Our algorithms tackle a varied & broad spectrum of challenges in the Wayfair marketplace; from empowering suppliers to easily add products to our catalog, to enabling our customers to discover and purchase a vast & diverse assortment of home goods, to driving marketing experiences customers love all at web scale.

We are looking for machine-learning scientists for research and development of the ML systems that power our real-time Search Typeahead, Search Guidance, Query Understanding & Interpretation, Query Refinement and Recommendations, and emerging GenAI-powered search capabilities . In this role, you’ll partner with fellow scientists, engineers, analysts, and product managers to apply science and machine learning skills to directly impact Wayfair’s revenue.

What you’ll do

• Design, build, deploy and refine large-scale machine learning models and algorithmic decision-making systems that solve real-world problems for customers
• Work cross-functionally with commercial stakeholders to understand business problems or opportunities and develop appropriately scoped analytical solutions
• Collaborate closely with various engineering, infrastructure, and ML platform teams to ensure adoption of best-practices in how we build and deploy scalable ML services
• Identify new opportunities and insights from the data (where can the models be improved? what is the projected ROI of a proposed modification?)
• Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on.

We Are a Match Because You Have

• Bachelor's degree with 4+ years of experience or Master’s degree with 3+ year of experience in Computer Science, Mathematics, Statistics, or related field.
• Strong theoretical understanding of statistical models such as regression, clustering and ML algorithms such as decision trees, neural networks, etc.
• Solid understanding of algorithms for search retrieval, ranking, relevance, query understanding, NLP, or recommender systems.
• Good proficiency in the Python ML ecosystem (pandas, NumPy, scikit-learn, XGBoost, etc.).
• Solid hands-on expertise deploying machine learning solutions into production
• Strong written and verbal communication skills.
• Intellectual curiosity and enthusiasm about continuous learning.

Nice to have

• Experience in e-commerce, or online search systems.
• Knowledge of modern NLP techniques (transformers, embeddings, semantic search).
• Experience applying Generative AI / LLMs (e.g., GPT, LLaMA) to real-world problems such as search, personalization, or content generation.
• Experience with deep learning frameworks like PyTorch.
• Familiarity with vector databases, information retrieval frameworks (e.g., Elasticsearch, Vespa)
• Familiarity with GCP (or AWS, Azure), ML model development frameworks, ML orchestration tools (Airflow, Kubeflow or MLFlow)
• Experience with Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML).