Principal ML System Engineer (Canada)

Location: Remote in Canada or Mississauga

Salary: US$176,000–US$195,000 base salary annually, plus bonus and benefits

Company

hirify.global develops healthcare technology and centralized machine learning platform capabilities for safe, scalable, and high-impact AI products.

What you will do

• Define the technical vision, strategy, reference architectures, standards, and multi-quarter roadmap for the company-wide ML platform.
• Design scalable data and ML pipelines covering model training, evaluation, deployment, serving, and monitoring.
• Set MLOps practices for model CI/CD, model registries, feature stores, experiment tracking, and build-versus-buy decisions.
• Establish reliability, observability, performance, security, access control, audit logging, and compliance practices for production ML systems.
• Define secure and cost-efficient integration patterns for APIs, data sources, and existing infrastructure.
• Provide technical leadership and mentorship across engineering teams and influence the organization-wide ML infrastructure roadmap.

Requirements

• Expert-level Python and Java skills with strong software engineering fundamentals.
• Deep experience designing and building ML platforms and MLOps workflows at scale.
• Experience with tools such as MLflow, Kubeflow, Ray, and model-serving frameworks or equivalents.
• Extensive experience with AWS, Azure, and/or GCP, as well as Docker and Kubernetes.
• Demonstrated experience setting technical direction and driving cross-team technical initiatives.
• Bachelor’s degree or higher in Computer Science, Machine Learning, or a related field is preferred.

Nice to have

• Familiarity with Azure Machine Learning, Databricks processing, serverless environments, and ML frameworks.
• Experience building and sustaining critical cross-team systems.
• Experience with role-based access control, multi-factor authentication, network security, and compliance monitoring.
• Experience optimizing large-model training and inference, including LLM serving, for performance and cost.

Culture & Benefits

• Remote workplace with an engineering team focused on centralized ML platform capabilities.
• Opportunity to influence technical standards and infrastructure practices across the organization.
• Base salary is part of a total rewards package that includes bonus and benefits.
• Compensation is assessed individually based on experience, skills, and market context.