Machine Learning Engineer

Responsibilities

• Optimize model inference for real-time recommendations.
• Containerize ML models using Docker/Kubernetes.
• Build REST APIs for the recommendation engine.
• Monitor model drift and retraining pipelines.
• Productionize machine learning models for fashion and fit recommendations, ensuring low-latency inference and high scalability.
• Deploy recommendation models using REST/gRPC APIs for real-time and batch inference.
• Optimize models for performance, memory usage, and response time in high-traffic environments
• Implement hybrid recommendation pipelines combining collaborative filtering, content-based filtering, and contextual signals (season, region, trends).
• Integrate stylist-curated rules and human-in-the-loop feedback into ML-driven recommendations.
• Support personalization based on body type, height, skin tone, ethnicity, and user style profiles.
• Build and mainta...