A company is looking for an Applied ML Scientist specializing in Model Calibration & Personalization.
Key Responsibilities
Fine-tune existing embeddings and learn weight calibration functions for cohesion scoring
Create context embeddings for rooms and users, and implement preference clustering
Define offline ranking metrics and design online A / B tests to evaluate model performance
Required Qualifications
4-8 years of applied ML experience in recommendation systems or personalization
MS / PhD preferred in Machine Learning, Computer Science, Applied Mathematics, or a related field
Strong technical expertise in PyTorch, XGBoost, and the Python data stack
Experience with multimodal embeddings and offline evaluation metrics
Background in e-commerce, fashion tech, home design, or digital advertising is a plus
Applied Scientist • Pasadena, California, United States