Machine Learning Scientist III - Catalog Science

Who We Are

Wayfair is an online retail platform with the mission to enable everyone to live in a home they love. Achieving this at global scale requires a high-quality well-structured product catalog that customers and internal systems can trust. Our Catalog Science team builds machine learning systems that power product discovery, reduce duplication, and streamline how suppliers add new products to Wayfairs catalog.

We are looking for a Machine Learning Scientist III with deep technical expertise and a proactive action-oriented mindset. In this role, you will be instrumental in developing and refining the advanced models and systems that power our core mission. You will join a cross-functional team of ML scientists, engineers, and product partners focused on understanding and organizing relationships across more than 41 million active SKUs. This role is a high-impact opportunity to develop advanced models and systems pioneering innovative solutions that directly influence customer experience, supplier efficiency, and downstream systems across search, merchandising, pricing, and fulfillment.

What Youll Do

Design, build, and deploy machine learning models that identify relationships between products in Wayfairs catalog, including duplicate and near-duplicate detection at massive scale.

Develop ML-driven solutions to improve the new product addition and supplier onboarding process, helping prevent duplicate listings and enriching product metadata at ingestion time.

Apply a mix of techniques, including representation learning, similarity search, classification, and graph-based methods, to model product relationships across structured and unstructured data attributes, text, images.

Conduct exploratory data analysis on large noisy retail datasets to uncover patterns, edge cases, and opportunities for model improvement.

Own end-to-end ML projects from problem formulation and experimentation through production deployment, monitoring, and iteration.

Define and track success metrics for catalog quality, duplication reduction, and supplier experience using data to continuously improve system performance.

Optimize cost efficiency and scalability of AI models leveraging parameter-efficient fine-tuning, LoRA, QLoRA, knowledge distillation, and hybrid ML approaches.

Collaborate with top AI research and industry leaders, e.g., Google Anthropic, Snorkel AI, to explore cutting-edge techniques in LLMs, data labeling automation, and scalable ML workflows.

Develop agentic AI workflows for automated schema definition, dataset generation, production relationship modeling, and LLM-based judgment systems to validate catalog data.

Mentor junior ML scientists and contribute to a culture of technical rigor, collaboration, and knowledge sharing.

Partner closely with product managers, supplier experience teams, and engineers to translate business needs into scalable ML solutions that integrate into production workflows.

We Are a Match

Because You Have

• A PhD with 3-5 years of experience or an MSc/BSc in a STEM field, Computer Science, Engineering, Data Science, or related, with 6-8 years of industry experience in applied machine learning.
• Strong proficiency in Python and the ML ecosystem, with hands-on experience using frameworks such as PyTorch, XGBoost, or similar.
• Proven experience deploying ML models into production, including collaboration with engineering partners and operating models at scale.
• Experience working with large, complex datasets and designing solutions that balance accuracy, latency, and cost.
• Deep understanding of data engineering concepts, with experience in building scalable data pipelines for collecting, processing, and transforming data.
• Strong written and verbal communication skills, with the ability to clearly explain technical concepts and influence cross-functional partners.
• Demonstrated ability to quickly learn new tools and techniques in a fast-paced, evolving environment, while managing multiple priorities with a high level of attention to detail and staying current with the latest ML research.

Nice to Have

• Experience with large-scale ecommerce or catalog data, including product attributes, taxonomy, text, and images.
• Familiarity with embedding-based similarity search, approximate nearest neighbors, or graph-based ML techniques.
• Experience with MLOps tooling, feature stores, MLflow, monitoring, and orchestration frameworks, Airflow, Kubeflow.
• Familiarity with cloud platforms, GCP, AWS, or Azure, and containerization tools, Docker.
• Exposure to LLMs or multimodal models for product understanding or data enrichment.

Why You Will Love Working With Us

Work on one of the largest and most complex retail catalogs in the world, with real, measurable impact on customers and suppliers.

Collaborate with talented scientists, engineers, and product leaders in a highly cross-functional environment.

Early adopters of new ML and AI technologies within Wayfair.

Hackathons and experimentation time to explore new ideas and approaches.

Benefits & Perks

• Fun team outings, like kayaking the Charles River and Boda Borg.
• Early adopters of new technology within Wayfair.
• Hackathons to explore new ideas.
• Time Off, Paid Holidays, Paid Time Off PTO, Health & Wellness, Full Health Benefits, Medical, Dental, Vision, HSA, Life Insurance, Disability Protection, Short Term & Long Term Disability, Global Wellbeing Gym, Fitness discounts, including US Peloton, Global ClassPass, and various regional gym memberships.
• Mental Health Support, Global Mental Health, Global Wayhealthy Recordings, Caregiver Services.
• Financial Growth & Security, 401K Matching, Employee Matching Program, Tuition Reimbursement, Financial Health Education, Knowledge of Financial Education - KOFE, Tax Advantaged Accounts, Family Support, Family Planning Support, Parental Leave, Global Surrogacy & Adoption Policy.
• Professional Development & Recognition, Rewards & Recognition, Global Employee Anniversary Awards, Paid Volunteer Work, Unique Perks, Employee Discount, U.S. Bluebikes Membership, Global Pod Outings, WorkLife Balance.

Emphasizing a supportive & flexible work environment that encourages a balance between personal and professional commitments.

Please note that this is a hybrid position based in Boston, MA. We are in-office Tuesday-Thursday and remote on Monday and Friday.

Assistance for Individuals with Disabilities

Wayfair is fully committed to providing equal opportunities for all individuals, including individuals with disabilities. As part of this commitment, Wayfair will make reasonable accommodations to the known physical or mental limitations of qualified individuals with disabilities, unless doing so would impose an undue hardship on business operations. If you require a reasonable accommodation to participate in the job application or interview process, please let us know by completing our Accommodations for Applicants form.

Need Technical Assistance

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About Wayfair Inc.

Wayfair is one of the worlds largest online destinations for the home. Whether you work in our global headquarters in Boston or in our warehouses or offices throughout the world, we are reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If youre looking for rapid growth, constant learning, and dynamic challenges, then youll find that amazing career opportunities are knocking.

No matter who you are, Wayfair is a place you can call home. We are a community of innovators, risk-takers, and trailblazers who celebrate our differences and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair - and world - for all. Every voice, every perspective matters. Thats why were proud to be an equal opportunity employer.

Your personal data is processed in accordance with our Candidate Privacy Notice https://www.wayfair.com/careers/privacy. If you have any questions or wish to exercise your rights under applicable privacy and data protection laws, please contact us at dataprotection@wayfair.com.