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.
Responsibilities
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 validation-ensuring 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.
Requirements
PhD with 0-1 years of experience or Masters 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 CICD, 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.
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 we are 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: 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.