Senior Machine Learning Systems Engineer

PointClickCare; United States; Remote; USD 170,000 - 230,000; Full time

Job summary

PointClickCare is seeking an experienced ML Platform Engineer to build and operate an internal ML platform powering AI products for post‑acute and long‑term care providers. You will own ML platform architecture, MLOps tooling, and production reliability, collaborating with product and engineering teams to deliver reusable capabilities.

You will design scalable data and ML pipelines, develop CI/CD for models, a model registry, feature stores, and experiment tracking, while ensuring security and

Qualifications

• Expert‑level proficiency in Python and Java with strong software engineering fundamentals.
• Hands-on experience designing and building ML platforms and MLOps workflows.
• Cloud experience, primarily Azure, with familiarity in AWS and GCP.
• Experience with containerization and orchestration of ML runtimes using Docker and Kubernetes.

Responsibilities

• Collaborate with product and engineering teams to translate ML needs into reliable, reusable platform capabilities.
• Design and build scalable data and ML pipelines covering training, evaluation, deployment, and serving.
• Develop MLOps tooling and workflows, including CI/CD for models, a model registry, feature stores, and experiment tracking.
• Ensure production reliability through monitoring, alerting, and automated remediation.
• Implement security mechanisms such as authentication, RBAC, audit logging, and compliance monitoring.
• Integrate the platform securely with existing systems, APIs, and data sources while optimizing cost, performance, and scale.
• Mentor engineers and promote reusable platform patterns and best practices.

Skills

Python

Java

MLOps

Data pipelines

Education

Bachelor's degree in CS or related

Tools

MLflow

Kubeflow

Ray

Model serving frameworks

Job description

Role overview

Build and operate the internal machine learning platform that powers AI products across a large health technology organization serving post-acute and long-term care providers. The role spans ML platform architecture, MLOps tooling, and production reliability, partnering closely with product and engineering teams to translate ML needs into reusable capabilities. It also contributes to safe, scalable AI/ML and LLM-based solutions used by tens of thousands of provider organizations.

Responsibilities

• Collaborate with product and engineering teams to translate ML needs into reliable, reusable platform capabilities
• Design and build scalable data and ML pipelines covering training, evaluation, deployment, and serving
• Develop MLOps tooling and workflows, including CI/CD for models, a model registry, feature stores, and experiment tracking
• Ensure production reliability through monitoring, alerting, and automated remediation
• Implement security mechanisms such as authentication, role-based access control, audit logging, and compliance monitoring
• Integrate the platform securely with existing systems, APIs, and data sources while optimizing cost, performance, and scale
• Mentor engineers and promote reusable platform patterns and best practices

Requirements

• Expert-level proficiency in Python and Java with strong software engineering fundamentals
• Hands‑on experience designing and building ML platforms and MLOps workflows, with familiarity in tools such as MLflow, Kubeflow, Ray, and model‑serving frameworks
• Cloud platform experience, primarily Azure, with secondary familiarity in AWS and GCP
• Experience with containerization and orchestration of ML runtimes using Docker and Kubernetes

Nice to have

• 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 RBAC, multi‑factor authentication, network security, and compliance monitoring
• Experience optimizing large model training and inference, including LLM serving, for performance and cost

Benefits and work setup

• Remote role with periodic travel to Mississauga and/or Salt Lake City offices for onboarding, team events, and semi‑annual and annual meetings
• Founder‑led, privately held company that reinvests a meaningful share of revenue into research and development