Improve the ranking and personalization of product recommendations across Wayfair's global search experience.
Requirements
- Expertise in recommendation systems, including candidate generation, ranking algorithms, and user-item modeling
- Deep understanding of collaborative filtering, sequence modeling, and embedding-based personalization
- Strong proficiency in Python and/or Java 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)
- Experience with workflow orchestration tools like Airflow, model tracking using MLflow, and containerization technologies like Docker
Responsibilities
- Design and implement scalable machine learning models to improve recommendation quality
- Develop robust retrieval systems to surface high-quality, personalized product recommendations at scale
- Apply deep learning and representation learning to model user preferences, product attributes, and contextual signals
- Explore sequence modeling, embeddings, and multi-modal modeling to drive the next generation of recommender systems
- Solve key issues such as the cold-start problem, data sparsity, product compatibility and seasonality in dynamic environments
- Collaborate with product managers, engineers, and data scientists to align recommendation strategies with business objectives and user needs
Other
- 3-6 years of experience as an ML engineer, applied scientist, or research scientist
- Bachelor's or advanced degree (Master’s, PhD) in Computer Science, Machine Learning, Mathematics, Statistics, or related field
- Strong written and verbal communication skills
- Time Off: Paid Holidays, Paid Time Off (PTO)
- Health & Wellness: Full Health Benefits, Life Insurance, Disability Protection
- Financial Growth & Security: 401K Matching, Tuition Reimbursement
