MLOps Engineer building production ML infrastructure, pipelines, and monitoring for exacare ai’s post - acute care AI platform. Scaling reliable systems that help healthcare teams make safer placement decisions.
About the role
- MLOps/LLMOps Architect designing AI solutions for a next-gen AI platform in Canada. Collaborating with teams on architecture, deployment, and governance in AI environments.
Responsibilities
- Design enterprise MLOps and LLMOps architecture
- Build deployment strategies for AI and LLM solutions
- Define model lifecycle management processes
- Implement monitoring, observability, and evaluation frameworks
- Design CI/CD pipelines for machine learning workloads
- Collaborate with AI researchers, platform engineers, and DevOps teams
- Support AI governance and security requirements
- Advise client stakeholders on operational AI best practices
Requirements
- 7+ years of experience in Machine Learning Engineering or MLOps
- 3+ years designing production-grade MLOps platforms
- Experience with LLM deployment and operationalization
- Strong knowledge of MLflow, Kubeflow, Vertex AI, Azure ML, SageMaker or similar platforms
- Experience deploying GenAI applications in enterprise environments
- Knowledge of RAG architectures, vector databases, model evaluation, and prompt management
- Experience with Kubernetes, Docker, CI/CD pipelines
- Familiarity with GPU infrastructure
- Strong understanding of AI governance and model lifecycle management
- Upper-Intermediate or higher level of English
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