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Added 8 mins ago
Senior Machine Learning Systems Engineer (CAD)
PointClickCare
Mississauga, ON
Full-time
The Senior Machine Learning Systems Engineer will work closely with the Product and Engineering teams to design, build, and operate the machine learning platform that enables teams across…
Added 23 mins ago
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Added 53 mins ago
Senior Machine Learning Systems Engineer (CAD)
PointClickCare
Mississauga, ON
$154,000 to $193,000 CAD / year
Full-time
The Senior Machine Learning Systems Engineer will work closely with the Product and Engineering teams to design, build, and operate the machine learning platform that enables teams across…
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161 Bay Street (93021), Canada, Toronto,Toronto, Ontario,Intern, Backend Software Engineer - Team Interstellar - Winter 2027
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PointClickCare

Senior Machine Learning Systems Engineer (CAD)

Mississauga, ON, Canada

Pay: $154,000 to $193,000 CAD / year
Job type: Full-time
Apply by: Oct 22, 2026
Posting language: English
Posted: Sep 22, 2026

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Original job description

At PointClickCare our mission is simple: to help providers deliver exceptional care. And that starts with our people. As a leading health tech company that’s founder-led and privately held, we empower our employees to push boundaries, innovate, and shape the future of healthcare.

With the largest long-term and post-acute care dataset and a Marketplace of 400+ integrated partners, our platform serves over 30,000 provider organizations, making a real difference in millions of lives. We also reinvest a significant percentage of our revenue back into research and development, ensuring our employees have the resources to innovate and make a lasting impact. Recognized by Forbes as a top private cloud company and honored as one of Canada’s Most Admired Corporate Cultures, we offer flexibility, growth opportunities, and meaningful work.

At PointClickCare, we empower our people to be the architects of a smarter healthcare future; one that is human-first and accelerated by AI to create meaningful and lasting change. Employees harness AI as a catalyst for creativity, productivity, and thoughtful decision-making. By integrating AI tools into our daily workflows, collaboration is enhanced, outcomes are improved, and every team member has the proficiency to maximize their impact. It all starts with our hiring practices where we uncover AI expertise that complements our mission, and we continue to invest in training and development to nurture innovation throughout the employee journey.

Join us in redefining healthcare - so it doesn’t just survive, it thrives. To learn more about PointClickCare, check out Life at PointClickCare and connect with us on Glassdoor and LinkedIn.

Travel to Office expectations**

For Remote Roles: If this role is remote, there will be in-office events that will require travel to and from the Mississauga and/or Salt Lake City office. These will include, but not limited to, onboarding, team events, semi-annual and annual team meetings.

For Hybrid Roles: If this role is Hybrid, there will be an expectation to reside within commutable distance to the office/location specified in the job listing. This will include, but not limited to, weekly/bi-weekly/monthly events in the office with your specific team. This is a requirement for this role.

Team Summary

This team will serve as the product owner for the machine learning platform capabilities within PointClickCare, working closely with other engineering teams across the organization to identify, build and support traditional machine learning (ML) and hybrid ML/LLMsolutions. This centralized team with deep specialization will closely integrate with key horizontal partners to ensure delivery of safe, scalable, and high-impact AI products.

Job Summary

The Senior Machine Learning Systems Engineer will work closely with the Product and Engineering teams to design, build, and operate the machine learning platform that enables teams across PointClickCare to develop, deploy, and scale ML solutions. The Senior AI Machine Learning Systems Engineer will also build and maintain the pipelines, tooling and infrastructure for model training, deployment, serving, and monitoring that underpin our AI products.

Key Responsibilities

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

Qualifications & Skills

Expert level in Python and Java, and strong software engineering fundamentals.
Experience designing and building ML platforms and MLOps workflows, with familiarity with tools such as MLflow, Kubeflow, Ray, and model-serving frameworks.
Experience with cloud platforms (Primarily Azure, secondarily AWS and GCP)
Experience with ML runtime containerization, optimization, and orchestration (Docker, Kubernetes).

Preferred

Bachelor’s degree or higher in Computer Science, Machine Learning, or a related field.
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 LLM serving) for performance and cost.

PointClickCare Benefits & Perks

Benefits starting from Day 1!

Retirement Plan Matching

Flexible Paid Time Off

Wellness Support Programs and Resources

Parental & Caregiver Leaves

Fertility & Adoption Support

Continuous Development Support Program

Employee Assistance Program

Allyship and Inclusion Communities

Employee Recognition … and more!

It is the policy of PointClickCare to ensure equal employment opportunity without discrimination or harassment on the basis of race, religion, national origin, status, age, sex, sexual orientation, gender identity or expression, marital or domestic/civil partnership status, disability, veteran status, genetic information, or any other basis protected by law. PointClickCare welcomes and encourages applications from people with disabilities. Accommodations are available upon request for candidates taking part in all aspects of the selection process. Please contact [email protected] should you require any accommodations. As part of our commitment to a streamlined and equitable hiring experience, PointClickCare uses AI tools to assist with candidate screening and assessment.

When you apply for a position, your information is processed and stored with Lever, in accordance with Lever’s Privacy Policy. We use this information to evaluate your candidacy for the posted position. We also store this information, and may use it in relation to future positions to which you apply, or which we believe may be relevant to you given your background. When we have no ongoing legitimate business need to process your information, we will either delete or anonymize it. If you have any questions about how PointClickCare uses or processes your information, or if you would like to ask to access, correct, or delete your information, please contact PointClickCare’s human resources team: [email protected]

PointClickCare is committed to Information Security. By applying to this position, if hired, you commit to following our information security policies and procedures and making every effort to secure confidential and/or sensitive information.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

At PointClickCare, base salary is one of the many components that make up our total rewards package. The CAD base salary range for this position is $154,000-$193, 000 (not overtime eligible) + bonus + benefits. Compensation is assessed individually and aligned to experience, skills, and market context. The posted range reflects typical expectations for this role

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More about this job

Responsibilities

The Senior Machine Learning Systems Engineer will design, build, and operate the machine learning platform to enable teams to develop, deploy, and scale ML solutions. They will also maintain pipelines, tooling, and infrastructure for model training, serving, and monitoring while ensuring system reliability and security.

Requirements

Candidates must have expert-level proficiency in Python and Java with strong software engineering fundamentals and experience in MLOps workflows. A bachelor's degree or higher in Computer Science, Machine Learning, or a related field is preferred.

Skills

Python
Java
Machine learning platforms
MLOps
MLflow
Kubeflow
Ray
Azure
Docker
Kubernetes
Data pipelines
Model training
Model serving
Security compliance
Infrastructure optimization
Mentoring

Benefits

Retirement plan matching
Flexible paid time off
Wellness support programs
Parental and caregiver leaves
Fertility and adoption support
Employee assistance program
Allyship and inclusion communities

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Systems Engineering
Python
Java
MLOps
MLflow
Kubeflow
Ray
Azure
AWS
GCP
Docker
Kubernetes
Databricks
LLM
CI/CD
Feature stores
Model registry
Infrastructure
Security
Compliance
Cloud computing
Data pipelines
Software engineering
Healthcare technology

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