Senior Machine Learning Engineer, Personalization & Decision Science
Core
Build and operate recommendation and optimization models for meal planning, shopping, and basket assembly that balance household constraints like budget, nutrition, and variety.
Role type
Senior individual-contributor machine learning engineer (personalization & decision science)
Builds
Multi-stage recommendation systems for recipes, products, meals, substitutions, and replenishment items
Domain
Grocery retail, meal planning, consumer e-commerce
Deliverable
production ML models
Required skills
recommender systems, mathematical optimization, forecasting, Python, SQL, experimentation, causal reasoning, production ML lifecycle management
Preferred skills
grocery/retail domain experience, constraint optimization, survival analysis, real-time systems
Technologies
collaborative filtering, two-tower retrieval, sequence models, learning-to-rank, contextual bandits
Responsibilities
Design and productionize multi-stage recommendation systems; model household preferences from interaction history; distinguish durable preferences from contextual exceptions; formulate multi-objective optimization for complete baskets; predict replenishment and substitutions; handle cold start and catalog variation; evaluate model performance at the basket level; own production pipelines and monitoring
Seniority
Senior, hands-on IC
