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 skilled 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 setting
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.

📌 Cloud Focused Mlops Engineer Role Toronto
🏢 Mphasis
📍 Toronto