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PointClickCare

Cloud-based EHR platform for post-acute care

Senior Machine Learning Systems Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeMississauga, ON, Canada

About the Job

Requirements

  • Expert-level proficiency in Python and Java, with strong software engineering fundamentals.
  • Experience designing and building machine-learning platforms and MLOps workflows, with familiarity with tools such as MLflow, Kubeflow, Ray, and model-serving frameworks.
  • Experience with cloud platforms, primarily Azure and secondarily AWS and GCP.
  • Experience with machine-learning runtime containerization, optimization, and orchestration using Docker and Kubernetes.
  • Working familiarity with Azure Machine Learning components and Databricks processing and serverless environments.
  • Experience implementing security at scale, including role-based access control, multi-factor authentication, network security best practices, and compliance monitoring.
  • Experience optimizing large-model training and inference, including large language model serving, for performance and cost.

Responsibilities

  • Collaborate with product and engineering teams to translate machine-learning needs into reliable, reusable platform capabilities.
  • Design and build scalable data and machine-learning pipelines that support model training, evaluation, deployment, and serving.
  • Develop and maintain MLOps tooling and workflows, including continuous integration and continuous delivery for models, model registry, feature stores, and experiment tracking.
  • Ensure the reliability, observability, and performance of machine-learning systems in production through monitoring, alerting, and automated remediation.
  • Implement security mechanisms for the machine-learning platform, including authentication, role-based access control, audit logging, and compliance monitoring.
  • Securely integrate the platform with existing systems, APIs, and data sources using secure communication protocols, and optimize infrastructure for cost, performance, and scale.
  • Mentor engineers on the teams and promote reusable platform patterns and best practices.

Desired Qualifications

  • Working familiarity with Azure Machine Learning components and Databricks processing and serverless environments.
  • Experience implementing security at scale, including role-based access control, multi-factor authentication, network security best practices, and compliance monitoring.
  • Experience optimizing large-model training and inference, including large language model serving, for performance and cost.

About the Company

PointClickCare

Cloud-based EHR platform for post-acute care

PointClickCare provides cloud-based software for senior care with a focus on electronic health records and care coordination. Its flagship Harmony platform connects post-acute care providers with acute care hospitals, enabling seamless exchange of clinical data to coordinate patient transitions. Harmony leverages a large post-acute care data cloud to deliver real-time insights and analytics that support informed decisions. The business runs on a subscription model, with additional revenue from training, support, and consulting, and it can integrate with other systems (such as Salesforce) to improve data interoperability. Compared with competitors, PointClickCare stands out by specializing in post-acute and senior-care settings, offering a broad data cloud and real-time analytics to drive better patient outcomes and operational efficiency. The company’s goal is to help healthcare organizations in senior care improve patient outcomes and streamline care coordination and delivery.

Company size
1,001-5,000
Company stage
Grant
Total funding
$226.2M
Headquarters
Mississauga, Canada
Founded
2000

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