Senior Machine Learning Systems Engineer (CAD)

Location: Hybrid in Mississauga, with residence within commutable distance to the office required

Base salary: CAD 154,000–193,000 plus bonus and benefits.

Company

hirify.global develops healthcare technology and provides a machine learning platform supporting traditional ML and hybrid ML/LLM products.

What you will do

• Design, build, and operate scalable machine learning platform capabilities for product and engineering teams.
• Develop data and ML pipelines for model training, evaluation, deployment, and serving.
• Build MLOps tooling and workflows, including model CI/CD, model registries, feature stores, and experiment tracking.
• Improve production reliability, observability, performance, and cost through monitoring, alerting, and automated remediation.
• Implement platform security through authentication, role-based access control, audit logging, and compliance monitoring.
• Mentor engineers and promote reusable platform patterns and best practices.

Requirements

• Expert-level Python and Java skills with strong software engineering fundamentals.
• Experience designing ML platforms and MLOps workflows using tools such as MLflow, Kubeflow, Ray, and model-serving frameworks.
• Experience with Azure, with additional exposure to AWS and GCP.
• Experience with Docker, Kubernetes, ML runtime containerization, optimization, and orchestration.
• Ability to collaborate with product and engineering teams to translate ML needs into reliable platform capabilities.

Nice to have

• Bachelor’s degree or higher in Computer Science, Machine Learning, or a related field.
• Familiarity with Azure Machine Learning, Databricks processing, and serverless environments.
• Experience implementing role-based access control, multifactor authentication, network security, and compliance monitoring at scale.
• Experience optimizing large-model training and inference, including LLM serving, for performance and cost.

Culture & Benefits

• Full-time employment with bonus and benefits.
• Hybrid work with regular team presence at the Mississauga office.
• Collaboration across engineering teams and horizontal platform partners.
• Opportunities to mentor engineers and establish reusable engineering practices.