Machine Learning Scientist II - Catalog Science

The Catalog Science team at Wayfair drives growth by tackling fundamental challenges ranging from multi-modal product understanding, product relationships modeling, to GenAI-driven catalog intelligence at scale. Our team provides the core capabilities that are crucial for enhancing the customer browse experience (e.g., visual search, recommendations), streamlining supplier product onboarding (e.g., product classification, image and content tagging), informing catalog competitiveness, and ultimately delivering significant impact for our customers, suppliers, and Wayfair. We are looking for a strong Machine Learning Scientist II 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 contribute to a diverse range of initiatives by applying cutting-edge deep learning techniques, vision-language models, and Generative AI agentic workflows. You will work in close collaboration with a highly capable, cross-functional team to tackle complex, high-impact challenges and help pioneer innovative solutions. If you are passionate about working on cutting-edge AI problems, building scalable machine learning systems that solve real-world challenges, and directly contributing to significant business impact, this is the role for you. What youu2019ll do: + Research and experiment with state-of-the-art multi-modal understanding techniques and algorithms. Design and implement evaluation strategies applied to real-world scenarios tailored to Wayfair use cases. + Leverage and fine-tune LLMs (e.g., OpenAI GPT, Google Gemini, Anthropic Claude, Open Source) to build AI-driven classifiers, product taggers, and quality control mechanisms. + Develop and refine the visual search system leveraging cutting edge technologies in computer vision, vision language models, and the large scale data orchestration. + Implement AI-powered automation for product data structuring, attribute extraction, and metadata validationu2014ensuring our catalog remains accurate, complete, and scalable. + 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. + Partner with cross-functional teams across engineering, scientists, and product to ensure AI solutions integrate seamlessly into catalog systems. + Optimize cost, efficiency, and scalability of AI models, leveraging parameter-efficient fine-tuning (LoRA, QLoRA), knowledge distillation, and hybrid ML approaches. Who you are: + PhD with 0-1+ years of experience or Masteru2019s in Computer Science, Machine Learning, or a related quantitative field with 2+ years of full-time industry experience in applied research. + Proven track record of delivering successful machine learning projects from conception to production, demonstrating strong deployment, problem-solving, and maintenance skills. + Deep understanding of both traditional Machine learning approaches and deep learning techniques, reinforcement learning, and multi-modal understanding. + Deep understanding of LLMs, generative AI, and fine-tuning techniques, and Retrieval-Augmented Generation (RAG) techniques, with hands-on experience using models like GPT, Gemini, Claude, etc. + Deep understanding of data engineering concepts with experience in building scalable data pipelines for collecting, processing, and transforming data. + Professional coding expertise in languages like Python and Go, proficiency in SQL, and experience with data visualization tools; skilled in using ML frameworks (TensorFlow, PyTorch) and implementing CI/CD, containerization, and version control best practices. + Familiarity with ML Ops, cloud infrastructure, and engineering best practices (Airflow, Kubeflow, MLFlow, Kubernetes, Spark, Python, SQL). + Excellent communication skills, with the ability to clearly articulate complex AI concepts to non-technical stakeholders while collaborating across teams. + 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: + Research publications in deep learning, computer vision, or generative AI. + Experience working in e-commerce catalog AI systems, retail data structuring, or large-scale product classification. + Background in autonomous AI agents, reinforcement learning, or online learning systems. Why Youu2019ll Love Wayfair: Time Off: + Paid Holidays + Paid Time Off (PTO) + Health & Wellness: + Full Health Benefits (Medical, Dental, Vision, HAS/FSA) + 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 u2013 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 Work/Life Balance: + Emphasizing a supportive & flexible work environment that encourages a balance between personal and professional commitments + Please note this is a hybrid position based in Boston, MA. Our teams 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 Accomodations for Applicants form (. Need Technical Assistance? For more information about applying for a career at wayfair, visit our FAQ page here (. About Wayfair Inc. Wayfair is one of the worldu2019s largest online destinations for the home. Whether you work in our global headquarters in Boston, or in our warehouses or offices throughout the world, weu2019re 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 youu2019re looking for rapid growth, constant learning, and dynamic challenges, then youu2019ll find that amazing career opportunities are knocking. No matter who you are, Wayfair is a place you can call home. Weu2019re 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 u2013 and world u2013 for all. Every voice, every perspective matters. Thatu2019s why weu2019re proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, genetic information, or any other legally protected characteristic. Your personal data is processed in accordance with our Candidate Privacy Notice (If you have any questions or wish to exercise your rights under applicable privacy and data protection laws, please contact us at .

Created: 2026-03-07