Machine Learning Scientist III - Ads + Search & Recommendations

Machine Learning Engineer The Ads + Search and Recommendations Machine Learning (ML) team at Wayfair is at the forefront of designing and implementing algorithms that define our global search experience. Using cutting-edge machine learning approaches, including deep sequence models, embeddings and multi-modal technologies, we aim to deliver a personalized and compelling experience for over 22 million active customers. Our mission is to make the user experience intuitive and efficient, helping customers discover exactly what they need in a vast and diverse product catalog. Wayfair's Advertising business is rapidly expanding, adding hundreds of millions of dollars in profits to Wayfair. We are building Sponsored Products, Display & Video Ad offerings that cater to a variety of Advertiser goals while showing highly relevant and engaging Ads to millions of customers. We are evolving our Ads Platform to empower advertisers across all sophistication levels to grow their business on Wayfair at a strong, positive ROI and are leveraging state of the art Machine Learning techniques. Wayfair is an online retail platform with the mission to enable everyone to live in a home they love. To do this, Wayfair builds and leverages cutting-edge Machine Learning and AI products and we are looking for talented individuals to join us. You will join the Customer Technology - Search & Recommendations org within its Advertising Footprint and Ranking team working on Candidate Generation and Retrieval Systems. You will be part of a cross-functional, collaborative team driving development of world-class ML systems that drive real-world impact. Here are some of the key projects our team works on: Candidate Generation/Retrieval: Selecting the right subset of products for our final scoring layers from our entire catalog efficiently through deep understanding of our product catalog and our customers at extreme scale using low latency situations across multiple types of Candidate Generators and Retrieval stages. This includes Generative Retrieval, Lightweight L1 Ranking, item-to-item methods (such as GCNNs), and many more! Scoring: Producing personalized scores like pCTR and pCVR for downstream ranking and footprint systems through state-of-the-art ML methods including deep learning, sequence transformers and LLMs (WaySeq) Ranking Optimization: Ordering Advertising products on the page given personalization, relevance and other factors (Profit Aware Ad Ranking) Footprint: Determining where Advertising goes on our website by optimizing the tradeoff between ad revenue and customer relevance (Ad Allocation at Scale) What You'll Do: Develop robust retrieval systems: Build and optimize candidate generation pipelines that surface high-quality, personalized product recommendations at scale. Leverage user and product signals: Apply deep learning and representation learning to model user preferences, product attributes, and contextual signals for better recommendation performance. Innovate with cutting-edge techniques: Explore sequence modeling, embeddings, and multi-modal modeling to drive the next generation of recommender systems. Collaborate cross-functionally: Partner with product managers, engineers, and data scientists to align recommendation strategies with business objectives and user needs. Tackle recommendation-specific challenges: Solve key issues such as the cold-start problem, data sparsity, product compatibility and seasonality in dynamic environments. Advance the ML community at Wayfair: Contribute to internal knowledge sharing, author technical documentation, and represent Wayfair at top ML conferences like Ads KDD, NeurIPS and RecSys. You Are a Fit If You Have: Minimum 2+ years of experience with PhD, or 4+ years of industry experience with MS, or 6+ years of experience with a BS in a quantitative STEM field. 1+ years of industry experience as an ML engineer, applied scientist, or research scientist, with a proven track record of delivering ML projects autonomously in recommendations, search, or ranking. Expertise in recommendation systems, including candidate generation, ranking algorithms, and user-item modeling. Deep understanding of techniques like sequence modeling, GCNNs, and/or embedding-based personalization. Experience with end-to-end project ownership, including collaboration with business partners and strong written and verbal communication skills. Strong proficiency in Python for building and deploying ML-driven recommendation systems. Experience deploying machine learning models in production environments, with a focus on cloud-based solutions such as GCP (BigQuery, GCS, Vertex AI, Composer), as well as workflow orchestration tools like Airflow, model tracking using MLflow, and containerization technologies like Docker. 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. About Wayfair Inc. Wayfair is one of the world's 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're 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 you're looking for rapid growth, constant learning, and dynamic challenges, then you'll find that amazing career opportunities are knocking. No matter who you are, Wayfair is a place you can call home. We're 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. That's why we're 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 View email address on click.appcast.io. Wayfair