(US) Principal ML System Engineer
Remote, USA
- Pay
USD 164,000–205,000/year · Base — pay source
#LI-remote At PointClickCare, base salary is one of the many components that make up our total rewards package. The US base salary range for this position is $164,000-$205, 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. Salary
Salary 164,000 – 205,000 USD per year PointClickCare Benefits & Perks:
Read the full posting- Work setting
Working pattern needs review — work setting source
**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.
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
Listed location: Remote, USA
Work setup in the employer’s listing: remote
From the employer’s posting- Employment
Full-time — employment source
Employment type Full-Time
Employment type in the employer’s listing: Full-Time
From the employer’s posting
What you’ll work on
Full postingTurn business goals into a multi-quarter ML platform strategy and roadmap
Define reference architectures and standards for ML pipelines and serving
Set MLOps direction, including CI/CD for models, registries, and feature stores
Establish reliability, observability, and monitoring practices for production ML
Design the ML platform security architecture, including access control and audit logging
From the employer’s posting
translate business and product objectives into a multi-quarter technical strategy and roadmap for the ML platform
Define the reference architectures and standards for scalable data and ML pipelines
Set the direction and best practices for MLOps across the company
Establish the practices and architecture for reliability, observability, and performance of ML systems in production
Establish the security architecture for the ML platform, including authentication, role-based access control, audit logging
Education & alternatives
Preferred - Bachelor’s degree or higher in Computer Science, Machine Learning, or a related field. - Sufficient familiarity with Azure Machine Learning components, Databricks processing and serverless environments, and ML Frameworks to support strategic decision making
Tools in this posting
- Java
- Python
- AWS
- Azure
- Databricks
- Docker
- Google Cloud (GCP)
- Kubernetes
- MLflow
Source — Tool mentions in context
Qualifications & Skills - Expert level in Python and Java with strong software engineering fundamentals. - Deep experience designing and building ML platforms and ML Ops workflows at scale, familiarity with tools such as MLFlow, Kubeflow, Ray, and model-serving frameworks or equivalents.
- Deep experience designing and building ML platforms and ML Ops workflows at scale, familiarity with tools such as MLFlow, Kubeflow, Ray, and model-serving frameworks or equivalents. - Extensive experience with cloud platforms (AWS, Azure, and/or GCP), containerization, and orchestration (Docker, Kubernetes). - Demonstrated track record of setting technical direction and driving org-wide technical initiatives across multiple teams.
- Bachelor’s degree or higher in Computer Science, Machine Learning, or a related field. - Sufficient familiarity with Azure Machine Learning components, Databricks processing and serverless environments, and ML Frameworks to support strategic decision making - Demonstrable history of leading and sustaining build out of critical cross-team systems
- Expert level in Python and Java with strong software engineering fundamentals. - Deep experience designing and building ML platforms and ML Ops workflows at scale, familiarity with tools such as MLFlow, Kubeflow, Ray, and model-serving frameworks or equivalents. - Extensive experience with cloud platforms (AWS, Azure, and/or GCP), containerization, and orchestration (Docker, Kubernetes).
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 13, 2026 · 66 days ago
- Recorded sightings
- 26
- Last seen by us
- Oct 18, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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Job description
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 Principal AI Machine Learning Platform Engineer will set the technical vision and strategy for the machine learning platform that powers ML and generative AI development across PointClickCare, partnering with Product and Engineering leadership to align that direction with product and business goals. As the technical authority for the ML platform, the Principal Engineer will define the reference architectures, standards, and roadmap for the pipelines, tooling, and infrastructure used for model training, deployment, serving, and monitoring, and will provide technical leadership and mentorship to raise the engineering bar for ML systems company-wide.
Key Responsibilities
- Partner with product and engineering leadership to translate business and product objectives into a multi-quarter technical strategy and roadmap for the ML platform.
- Define the reference architectures and standards for scalable data and ML pipelines spanning model training, evaluation, deployment, and serving that engineering teams across the organization build upon.
- Set the direction and best practices for MLOps across the company — including CI/CD for models, model registry, feature stores, and experiment tracking — and drive build-vs-buy decisions for core platform components.
- Establish the practices and architecture for reliability, observability, and performance of ML systems in production, including monitoring, alerting, and automated remediation.
- Establish the security architecture for the ML platform, including authentication, role-based access control, audit logging, and compliance monitoring, and ensure adoption across teams.
- Define secure, cost-efficient integration and infrastructure patterns for connecting the platform with existing systems, APIs, and data sources at scale.
- Provide technical leadership and mentorship across engineering teams, guiding senior engineers and influencing the org-wide technical roadmap for ML infrastructure.
Qualifications & Skills
- Expert level in Python and Java with strong software engineering fundamentals.
- Deep experience designing and building ML platforms and ML Ops workflows at scale, familiarity with tools such as MLFlow, Kubeflow, Ray, and model-serving frameworks or equivalents.
- Extensive experience with cloud platforms (AWS, Azure, and/or GCP), containerization, and orchestration (Docker, Kubernetes).
- Demonstrated track record of setting technical direction and driving org-wide technical initiatives across multiple teams.
Preferred
- Bachelor’s degree or higher in Computer Science, Machine Learning, or a related field.
- Sufficient familiarity with Azure Machine Learning components, Databricks processing and serverless environments, and ML Frameworks to support strategic decision making
- Demonstrable history of leading and sustaining build out of critical cross-team systems
- 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.
Salary
164,000 – 205,000 USD per year
Employment type
Full-Time
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
#LI-remote At PointClickCare, base salary is one of the many components that make up our total rewards package. The US base salary range for this position is $164,000-$205, 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. Salary
More source context
Salary 164,000 – 205,000 USD per year PointClickCare Benefits & Perks:
- Location & working pattern
Remote, USA
**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
More source context
#LI-AJ1 #LI-remote At PointClickCare, base salary is one of the many components that make up our total rewards package. The US base salary range for this position is $164,000-$205, 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.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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