Job Description
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:
- 3+ years of industry experience with a Bachelor/ Master’s degree or minimum of 1-2 years of industry experience with PhD 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).