Senior Machine Learning Scientist - Agentic Merch

Wayfair; Boston (MA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Parental Leave

Job summary

Wayfair is seeking a Senior Machine Learning Scientist to shape the roadmap of our Agentic Curation and Assortment Engine. You will collaborate with engineers, product, and business partners to model relationships across millions of SKUs and translate insights into scalable ML workflows.

Lead end-to-end projects from problem formulation to production deployment, mentor junior scientists, and drive data-driven improvements that influence Wayfair’s merchandising strategy and customer experience.

Qualifications

• PhD required or 9+ years with MS, 10+ years with BS in STEM.
• Experience leading ML projects and deploying models at scale.
• Expertise in graph-based ML and agentic workflows.

Responsibilities

• Design, build, and deploy ML models to optimize product mix.
• Use representation learning, similarity search, and graphs on multimodal data.
• Improve model cost, efficiency, and production readiness.
• Lead end-to-end ML projects from problem framing to production.
• Define success metrics for curation and assortment.
• Collaborate with AI research and industry leaders.
• Develop agentic AI workflows for schema and data generation.
• Mentor junior ML scientists.
• Partner with product and engineering to productionize ML solutions.

Skills

Python

PyTorch

XGBoost

Graph ML

LLMs

Model deployment

MLOps

Experimentation

Education

PhD

MS in STEM

BS in STEM

Tools

Git

Docker

Kubernetes

Job description

• Parental Leave
• Unique Perks:

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