Machine Learning Scientist

Wayfair - Boston, MA

Full-time - Mid Level

Boston, MA

1,001-5,000 employees

Furniture, Home Furnishings, Electronics, and Appliance Retailers

About the position

Wayfair is seeking machine-learning scientists to enhance its global search experience and recommendation services. The role involves designing, building, and deploying large-scale machine learning models to solve real-world customer problems, while collaborating with cross-functional teams to drive impactful solutions. The ideal candidate will have deep expertise in NLP, deep learning, or search and information retrieval, and will contribute to improving customer experiences for over 22 million active users.

Responsibilities

• Design, build, deploy and refine large-scale machine learning models and algorithmic decision-making systems.
• Work cross-functionally with commercial stakeholders to understand business problems and develop analytical solutions.
• Collaborate with engineering, infrastructure, and ML platform teams to ensure best practices in scalable ML services.
• Identify new opportunities and insights from data to improve models and assess projected ROI of modifications.
• Maintain a customer-centric approach in problem-solving and decision-making.
• Mentor and foster the development of junior ML scientists on the team.

Requirements

• Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related field.
• 5-7 years of industry experience in developing machine learning algorithms and deploying them into production at web scale.
• Proficiency in Python or another high-level programming language.
• Familiarity with productionized code bases and PRs; comfort mentoring junior scientists.
• Concrete hands-on expertise deploying machine learning solutions into production.
• Theoretical understanding of statistical models and ML algorithms such as regression, clustering, decision trees, and neural networks.
• Deep domain knowledge in NLP, Deep Learning, or Search & Information Retrieval.
• Strong written and verbal communication skills with a bias towards simplicity.
• Intellectual curiosity and enthusiasm for continuous learning.

Nice-to-haves

• Ph.D. in a quantitative field with a track record of relevant publications.
• Experience with Python ML ecosystem (numpy, pandas, sklearn, XGBoost, etc.).
• Familiarity with cloud ML tooling (GCP, AWS, Azure) and ML orchestration tools (Airflow, Kubeflow, MLFlow).
• Expertise in information retrieval, query/intent understanding, search ranking, and recommender systems.

Benefits

• Rapid growth opportunities
• Continuous learning environment
• Dynamic challenges in a supportive community