Apply machine learning reliability expertise at BMO’s hybrid 33 Dundas Street West workplace, focusing on automation, monitoring, and model performance. This Senior AI Engineer develops machine learning and deep learning systems for complex, non-deterministic models. You will run experiments, retrain systems, extend frameworks, and analyze extensive historical data. The position also supports observability pipelines, centralized dashboards, statistical testing, and production incident analysis. Key Responsibilities:
Develop machine learning applications and algorithms Run experiments, tests, and statistical analysis Retrain systems to prevent model drift Optimize machine learning libraries and frameworks Perform root cause analysis for AI failures Requirements:
Bachelor's degree in a relevant technical domain Seven to ten years of Site Reliability Engineering experience Highly proficient in automation, monitoring, and observability Understanding of model architectures and evaluation metrics Exposure to heavily regulated industry organizations Bring machine learning, reliability engineering, and observability skills to BMO’s production AI systems and analytical services.
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Senior Machine Learning Reliability Engineer in Toronto employer: Aimlroles
Procurify is an exceptional employer that fosters a collaborative and innovative work culture, allowing you to thrive as an AI Engineering Manager. With a remote-first approach, you'll enjoy the flexibility of working from anywhere in Canada while benefiting from continuous professional development opportunities and a supportive team environment that values your contributions. Join us to lead cutting-edge AI initiatives and make a meaningful impact in a company that prioritizes employee growth and well-being.
