Senior ML Platform Engineer - Scalable AI Systems

Lever, Inc.; Northern (KY); Hybrid; USD 174,000 - 218,000; Full time

Benefits offered by this job

Benefits starting from Day 1!

Retirement Plan Matching

Flexible Paid Time Off

Wellness Support Programs

Job summary

PointClickCare is seeking a Senior Machine Learning Systems Engineer to design, build, and operate the ML platform enabling cross-team ML solutions. You will develop pipelines, tooling, and infrastructure for training, deployment, serving, and monitoring of AI products.

You will work with Product and Engineering, mentor teammates, and help ensure scalable, secure ML systems with cost-aware infrastructure across cloud environments.

Qualifications

• Expert level in Python and Java with strong software engineering fundamentals.
• Experience designing ML platforms and MLOps workflows with relevant tools.
• Experience with cloud platforms (Azure, AWS, GCP) and container orchestration.

Responsibilities

• Collaborate with product and engineering teams to translate ML needs into platform capabilities.
• Design and build scalable data and ML pipelines for training, evaluation, deployment, and serving.
• Develop and maintain ML Ops tooling and workflows, including CI/CD for models and experiment tracking.
• Ensure reliability, observability, and performance of ML systems in production.
• Implement security mechanisms for the ML platform, including access control and compliance monitoring.
• Mentor engineers and promote reusable platform patterns and best practices.

Skills

Python

Java

ML platforms

CI/CD

Education

Bachelor’s degree or higher in Computer Science or ML

Tools

MLflow

Kubeflow

Ray

Docker

Kubernetes

Model-serving frameworks

Job description

PointClickCare is seeking a Senior Machine Learning Systems Engineer to design, build, and operate the ML platform enabling cross-team ML solutions. You will develop pipelines, tooling, and infrastructure for training, deployment, serving, and monitoring of AI products.

You will work with Product and Engineering, mentor teammates, and help ensure scalable, secure ML systems with cost-aware infrastructure across cloud environments.