Found Description
Join a cutting-edge team as a Senior ML Engineer focused on building ML pipelines in Toronto. This role emphasizes MLOps best practices while elevating Trust Scoring model efficiency.
In this hands-on position, you'll spearhead the design and production of ML systems within an AWS-native environment. Collaborate closely with feature engineering teams to ensure high-quality data and model outputs. You'll engage in both batch and real-time scoring workflows while monitoring model performance and addressing feature drift, ensuring adherence to industry standards.
Key Responsibilities: • Transform PoC ML models into production-ready pipelines • Execute deterministic preprocessing for reliable outputs • Maintain CI/CD pipelines within MLOps • Generate explainability artifacts for models • Support model performance monitoring and validation
Requirements: • 3–5 years of Machine Learning experience • Proficient in Python and PySpark • Strong AWS skills, including IAM...
In this hands-on position, you'll spearhead the design and production of ML systems within an AWS-native environment. Collaborate closely with feature engineering teams to ensure high-quality data and model outputs. You'll engage in both batch and real-time scoring workflows while monitoring model performance and addressing feature drift, ensuring adherence to industry standards.
Key Responsibilities: • Transform PoC ML models into production-ready pipelines • Execute deterministic preprocessing for reliable outputs • Maintain CI/CD pipelines within MLOps • Generate explainability artifacts for models • Support model performance monitoring and validation
Requirements: • 3–5 years of Machine Learning experience • Proficient in Python and PySpark • Strong AWS skills, including IAM...