Job Description Role Mission: To accelerate the delivery of AI/ML prototypes into production by writing clean, testable code and building scalable data pipelines. Accountabilities: Code Quality & Delivery: Own the delivery of well-documented, unit-tested features for AI-powered applications. Data Pipeline Stability: Ensure the reliability of data ingestion and preprocessing workflows feeding into ML models. Model Integration: Bridge the gap between data science notebooks and production APIs/services.
Responsibilities: Design, develop, and maintain backend services and APIs to serve machine learning models in production. Write efficient code to transform, clean, and aggregate large datasets for model training and inference. Collaborate with Data Scientists to refactor prototype code (Python/notebooks) into production-ready modules. Implement logging, monitoring, and alerting for AI services to ensure high availability. Participate in code reviews and contribute to engineering playboo...