Who we are

Wayfair is moving the world so that anyone can live in a home they love. This journey is enabled by more than 3,000 Wayfair engineers and a data-centric culture.

The Customer Technology (CT) Science team builds and owns machine learning products that power search, marketing, and recommendations across Wayfair. Our algorithms address a broad range of challenges in the Wayfair marketplace, from helping suppliers add products to our catalog to enabling customers to discover and purchase a vast assortment of home goods and delivering marketing experiences customers love, all at web scale.

We are looking for an experienced Machine Learning Scientist to develop the next generation of personalization and customer understanding systems at Wayfair. You will build large-scale models that learn from billions of customer interactions to improve content recommendations, personalized search, and product discovery. You will also create reusable customer representations that support experiences across the Wayfair ecosystem.

In this role, you will own machine learning solutions end to end, from problem definition and hypothesis testing to model development, evaluation, and production deployment. You will partner closely with engineers, product managers, platform teams, and scientists to solve complex challenges in representation learning, ranking, retrieval, and personalization. Your work will translate advances in machine learning research into scalable capabilities used across search, recommendations, marketing, and other customer-facing products, improving relevance and discovery for millions of customers.

What you'll do

Design, train, evaluate, and deploy large-scale machine learning models for customer understanding, personalization, search, and recommendations.
Evaluate and adapt advances in recommendation systems, representation learning, large language models, and foundation models to solve practical customer and business problems.
Develop rigorous offline evaluation frameworks and design online A/B tests to measure customer and business impact.
Collaborate with product, engineering, and analytics teams to translate ambiguous customer needs into well-defined machine learning problems.
Partner with engineers to productionize models and build reliable, scalable training and inference pipelines.
Monitor model performance, identify opportunities for improvement, and continuously iterate on models in production.

What you'll need

A bachelor's degree in Computer Science, Mathematics, Statistics, or a related field with 7+ years of relevant industry experience; or a master's degree in a related field with 6+ years of relevant industry experience.
Proven experience building and deploying machine learning models in production at scale.
Strong knowledge of machine learning, statistics, optimization, and modern deep learning techniques.
Experience designing, training, and evaluating models using large-scale datasets.
Proficiency in Python and experience with machine learning frameworks such as PyTorch or TensorFlow.
Strong software engineering fundamentals and experience partnering with engineering teams to build reliable, scalable ML systems.
Excellent written and verbal communication skills, with the ability to explain complex technical concepts to a range of audiences.
Intellectual curiosity and a commitment to continuous learning.

Nice to have

Experience building recommender systems, personalization models, retrieval and ranking systems, or customer understanding models.
Experience with representation learning, embeddings, contrastive learning, sequence modeling, or transformer architectures.
Experience with distributed model training and large-scale retrieval and inference pipelines.
Experience with cloud platforms such as GCP, AWS, or Azure.
Familiarity with MLOps and workflow orchestration tools such as Airflow, Kubeflow, MLflow, or Vertex AI.
Experience applying large language models or generative AI techniques to personalization, search, or recommendation problems.

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.

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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 (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 [HIDDEN TEXT].

Machine Learning Scientist III - Customer Technology