Job Description
Elevate your career with this Senior ML Engineer role focusing on Trust Scoring platforms in Toronto. Drive the design and productionization of ML pipelines while utilizing best practices in MLOps.
In this full-time role, you will be responsible for building and managing robust ML pipelines within an AWS-native architecture. This hands-on position involves batch inference, real-time scoring, and facilitating explainability measures. Your expertise in model productionization and collaboration with data engineering teams will be crucial in ensuring data quality and performance efficacy.
Key Responsibilities:
• Productionize PoC ML models into governed pipelines
• Develop batch and near-real-time inference workflows
• Implement MLflow for model management
• Design features from batch and low-latency stores
• Monitor model performance and feature drift
Requirements:
• 3–5 years as a Machine Learning Engineer
•...
In this full-time role, you will be responsible for building and managing robust ML pipelines within an AWS-native architecture. This hands-on position involves batch inference, real-time scoring, and facilitating explainability measures. Your expertise in model productionization and collaboration with data engineering teams will be crucial in ensuring data quality and performance efficacy.
Key Responsibilities:
• Productionize PoC ML models into governed pipelines
• Develop batch and near-real-time inference workflows
• Implement MLflow for model management
• Design features from batch and low-latency stores
• Monitor model performance and feature drift
Requirements:
• 3–5 years as a Machine Learning Engineer
•...