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(Canada) Principal ML System Engineer

1 month ago
Canada
Full-time
Lead
Machine Learning Engineer
DevOps and Infrastructure
AWS Azure CI/CD Databricks Docker GCP Java Kubeflow Kubernetes Machine Learning MLflow MLOps Network Security Python Serverless
Apply Now
PointClickCare

PointClickCare

PointClickCare provides a leading cloud-based healthcare software platform that enables long-term and post-acute care providers to effectively manage the complete lifecycle of resident care while enhancing operational efficiency and improving resident ...

Health Care Providers & Services
1K-5K
Founded 2000
$232M raised
View All Jobs 46

Description

  • Partner with product and engineering leadership to define a multi-quarter technical strategy and roadmap for the ML platform.
  • Define reference architectures and standards for scalable data and ML pipelines for training, evaluation, deployment, and serving.
  • Set MLOps direction and best practices across the company, including CI/CD, model registry, feature stores, and experiment tracking.
  • Drive build-versus-buy decisions for core ML platform components.
  • Establish reliability, observability, and performance practices for production ML systems, including monitoring, alerting, and automated remediation.
  • Define the security architecture for the ML platform, including authentication, role-based access control, audit logging, and compliance monitoring.
  • Create secure and cost-efficient integration patterns for connecting the platform to existing systems, APIs, and data sources at scale.
  • Provide technical leadership and mentorship across engineering teams and influence the org-wide roadmap for ML infrastructure.

Requirements

  • Expert-level proficiency in Python and Java with strong software engineering fundamentals.
  • Deep experience designing and building ML platforms and MLOps workflows at scale.
  • Familiarity with ML tools such as MLflow, Kubeflow, Ray, and model-serving frameworks or equivalents.
  • Extensive experience with cloud platforms such as AWS, Azure, and/or GCP.
  • Experience with containerization and orchestration tools such as Docker and Kubernetes.
  • Demonstrated track record of setting technical direction and driving org-wide initiatives across multiple teams.
  • Bachelor’s degree or higher in Computer Science, Machine Learning, or a related field (preferred).
  • Familiarity with Azure Machine Learning, Databricks processing, and serverless environments (preferred).
  • Experience leading and sustaining the buildout of critical cross-team systems (preferred).
  • Experience implementing security at scale, including RBAC, MFA, network security best practices, and compliance monitoring (preferred).
  • Experience optimizing large model training and inference, including LLM serving, for performance and cost (preferred).

Interested in this position?

Apply directly on the company website

Apply Now

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