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 professional 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