Become a pivotal Cloud-focused MLOps Engineer, dedicated to developing and monitoring ML and LLM pipelines in Canada, utilizing the latest cloud technologies.
This role is ideal for a qualified with more than a decade of hands-on MLOps experience. You will focus on building end-to-end ML pipelines, leveraging open-source automation tools, and ensuring workflows are optimized in cloud environments like GCP and AWS. Your work will directly influence model performance and deployment efficiency.
Key Responsibilities:
• Implement end-to-end ML/LLM pipelines and monitor them
• Automate workflows with open-source tools such as Kubeflow
• Manage CI/CD processes for ML model deployment
• Use observability tools to track model performance
• Support cross-functional collaboration for enhanced pipelines
Requirements:
• Minimum 10 years in MLOps environment
• Familiarity with AI platforms AWS, GCP, or Azure
• Proficient in Python and infrastructure as code tools
• Experience with ML frameworks like TensorFlow or PyTorch
• Degree in a relevant quantitative field
Drive your career forward by enhancing ML processes in a cloud landscape as an MLOps Engineer.
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📌 Cloud-focused MLOps Engineer Role (Toronto)
🏢 Mphasis
📍 Toronto