Senior Machine Learning Scientist - Agentic Merch

Who We Are Wayfair is an online retail platform with a mission to enable everyone to live in a home they love. Achieving this at global scale requires building science\-backed solutions that continuously map customer demand, recommend shelf actions, and optimize curated assortments across various online and offline Wayfair commercial channels and programs. We are looking for a Senior Machine Learning Scientist with deep technical expertise and a proactive, action\-oriented mindset. In this role, you will be instrumental in shaping the roadmap of the Agentic Curation and Assortment Engine that powers our core mission. You will join a growing team of ML scientists, working closely with engineers, business, and product partners, understanding customer demand, identifying missing selection and curation gaps, and organizing product relationships across more than 41 million active SKUs. This role is a high\-impact opportunity to develop advanced models, scalable toolings, and agentic merchandising workflows (e.g. line planning, sourcing, event curation) that directly influence Wayfair’s business strategy and contribute to the customer centric mission. What You’ll Do \* Design, build, and deploy machine learning models that identify relationships between products in Wayfair’s catalog and external trends, and optimize the product mix for the right demand. \* 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). \* Optimize cost, efficiency, and scalability of AI models, leveraging parameter\-efficient fine\-tuning (LoRA, QLoRA), knowledge distillation, and hybrid ML approaches. \* 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 product grouping quality, product curation success, assortment gap identification, using data to continuously improve system performance. \* 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 \* Minimum 5\+ years of experience with PhD, or 9\+ years of industry experience with MS, or 10\+ years of experience with a BS in a quantitative STEM field. \* 2\+ years of experience working as a Tech Lead, preferably developing agentic AI workflows at scale. \* 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. \* Deep expertise in building and scaling graph relationships based on structured and unstructured data and agentic workflows to uncover customer demand, organize products to demand spaces, and drive automated gap identification. \* Hands\-on experience with representation learning, embedding\-based similarity search, and graph\-based ML to construct demand huddles and model product substitutability across multimodal data (text, images, attributes). \* Demonstrated ability to design and deploy agentic AI workflows and LLM\-based judgment systems for scalable curation, schema definition, and automated catalog validation. \* Experience working with large, complex datasets and scalable data pipelines, balancing model accuracy, latency, and operational cost efficiency. \* Strong written and verbal communication skills, with the ability to clearly explain technical concepts and influence cross\-functional merchant, product, and engineering partners. 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/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 \- 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