Senior Machine Learning Scientist - Recommendations

We are looking for an experienced Senior Machine Learning Scientist to join our Content Recommendations team. In this role, you will be at the core of building and optimizing ML-based recommender systems (e.g., image and content recommendations, homepage and email optimization and personalization) to enhance the customer experience at Wayfair. Your work will directly impact how millions of customers discover and engage with products, driving significant business value. What You’ll Do Develop and optimize recommendation models that power personalized experiences across Wayfair’s site, app, email, and push notifications. Conduct applied research to improve recommender systems using traditional ML techniques, deep learning and reinforcement learning. Build scalable ML pipelines for training, evaluation, and inference, ensuring models operate efficiently in production. Work closely with engineering teams to deploy models in a production environment, addressing real-world constraints such as latency, interpretability, and scalability. Analyze model performance and iterate based on A/B test results, offline evaluation metrics, and business impact. Leverage and contribute to open-source ML frameworks while staying up to date with cutting‑edge research in recommendation systems. Drive innovation by identifying opportunities to improve personalization strategies and developing novel algorithms that enhance customer engagement. Collaborate with cross‑functional teams including product managers, software engineers, and data scientists to align ML objectives with business goals. Mentor other less experienced scientists. Who You Are 7+ years of experience developing and deploying machine learning models, with a focus on recommendations, ranking, or personalization. Strong theoretical understanding of machine learning and deep learning applied to large‑scale recommendation problems. Experience in training, evaluating, and optimizing recommendation models in production, leveraging techniques such as collaborative filtering, sequence modeling, representation learning and multi‑armed bandits. Proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit‑Learn. Familiarity with big data processing (Spark, Hadoop) and ML pipeline orchestration (Airflow, Kubeflow, MLflow). Strong coding skills and familiarity with building scalable ML systems in cloud environments (AWS, GCP, Azure). Ability to design experiments and analyze results using A/B testing and statistical techniques. Excellent communication skills, with the ability to explain complex ML concepts to non‑technical stakeholders and drive data‑driven decisions. Nice to Have Experience developing core recommendation systems for eCommerce, marketplaces, or streaming platforms. Familiarity with reinforcement learning or contextual bandits for adaptive recommendation strategies. This role offers the opportunity to work on high‑impact ML problems at scale, shaping the future of personalization and recommendations at Wayfair. If you're passionate about building intelligent systems that enhance customer experiences, we’d love to hear from you! Benefits 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 Wayfair’s In‑Office Policy All Mountain View‑based interns, co‑ops, and corporate employees will be in office in a hybrid capacity. Employees will work in the office on designated days, Tuesday, Wednesday, and Thursday, and work remotely the other 2 days of the week. 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. 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. #J-18808-Ljbffr Wayfair