ML Engineer (with full stack capabilities) and Phone screen criteria [] Responsibilities Design, experiment and deploy AI/ML models with intent in a fast-paced environment Monitoring and evaluating ML model performance [] Qualifications (purposefully light) BS in Engineering or Computer Science Comfortable in Python and SQL Foundational understanding of statistics and probability Systematic, structured thought process Experience with ML Frameworks: Scikit-learn, PyTorch [Phone Screen] 2 hard requirements to screen for when meeting them: Have they built and deployed models from notebook to production that's serving real traffic today? Please capture experiences where they have experimentation and deployment experience and the level of complexity of the integrations necessary. Experimentation takes precedence.

This aims to eliminate candidates who look great on paper but we need vigente ML in production experiences. How are they currently using AI coding tools, and what was their experience when they noticed a weakness and how did they go about it. Please screen for lack of excitement and very generic, vague answers.

📌 Analytics Data science and IOT Lead (México)
🏢 Hexaware
📍 México