Machine Learning Engineer Applied AI

Build production machine learning solutions with Python and SQL at Zurich Canada, supporting scalable AI engineering across multiple experience levels.

Machine Learning Engineers design, develop, and operationalize secure, reliable solutions within a modern cloud data and AI ecosystem. Applied AI work includes predictive modeling, feature engineering, model evaluation, inference optimization, and production monitoring. Candidates may be Junior, Intermediate, or Senior, based on experience and technical depth.

Key Responsibilities:

• Build and productionize classification, regression, forecasting, and clustering models
• Develop feature pipelines and training validation testing processes
• Evaluate models and optimize batch or real time inference
• Monitor data quality, performance drift, and production issues
• Document assumptions, limitations, versions, data references, and approvals

Requirements:

• Python and SQL skills
• Understanding of machine learning concepts and development lifecycle
• Software engineering fundamentals, including Git, APIs, testing, and CI/CD
• Experience with data processing and analytical workloads
• Cloud based development experience and production readiness understanding

Apply machine learning, feature engineering, and model evaluation skills to production-ready AI solutions at Zurich Canada.