Staff Applied Scientist - Search & Personalization

About the role

The Staff Applied Scientist - Search & Personalization position is located in Mountain View, California. This role falls under the Data Science & Machine Learning category. The annual base pay range is USD 216,000.00 - USD 228,000.00, which may vary based on location, experience, and other factors. Wayfair offers a comprehensive suite of medical, financial, and additional benefits.

Responsibilities

• Enhance search relevance: Design and implement scalable ML models to improve search results.
• Optimize retrieval systems: Develop and fine-tune search retrieval techniques for web-scale customer queries.
• Advance query understanding: Apply advanced NLP techniques for enhanced query parsing, intent recognition, and semantic understanding.
• Innovate search experiences: Explore and implement graph-based learning, semantic embeddings, and multi-modal techniques for next-generation search systems.
• Collaborate cross-functionally: Work with product managers, engineers, and data scientists to align search system improvements with business goals.
• Solve unique search challenges: Address issues such as cold-start problems, long-tail queries, and real-time search performance optimization.
• Contribute to the community: Share expertise through internal forums, author technical documentation, and represent Wayfair at leading ML conferences.

Qualifications

• Expertise in search technologies, including retrieval, ranking systems, and query understanding.
• Strong proficiency in Python and/or Java for building and deploying ML-driven search systems.
• Deep understanding of NLP techniques, semantic search, and embedding-based retrieval.
• Proven ability to execute and deliver large-scale search-related ML projects, including roadmap development and implementation.
• Strong knowledge of statistical modeling, experimental design, hypothesis testing, or optimization.
• Experience with cloud-native technologies; familiarity with GCP and Vertex AI is a plus.
• Advanced problem-solving skills focused on search-specific challenges like personalization, scalability, and accuracy.

Preferred Skills

• Familiarity with e-commerce search systems or similar large-scale applications.
• Experience in applying graph-based learning and multi-modal techniques to search.
• Practical expertise in designing scalable, reusable, and cloud-based search infrastructures.
• Contributions to internal forums or external ML and search-focused communities.