Principal DevOps Engineer (AI/ML Infrastructure) - Remote Canada

revvity; United States; Remote; USD 91,000 - 116,000; Full time

Job summary

revvity is seeking a Senior Engineer to lead the design and operation of infrastructure for AI and ML within a scientific software platform. The role unites research and software engineering to enable reliable model building, testing, deployment, and monitoring at scale.

You will architect scalable, secure infra; push for robust CI/CD pipelines across data ingestion, deployment, serving, and monitoring; and mentor junior engineers while aligning platform practices with research goals.

Qualifications

• Minimum 5 years in DevOps, ML infrastructure, or platform engineering with leadership experience.
• Deep experience with a major cloud provider and its AI/ML and container services.
• Hands-on with ML orchestration platforms such as Kubeflow, MLflow, or SageMaker.
• Strong automation skills in Python, Go, or Bash.
• Excellent collaboration with researchers and engineers.

Responsibilities

• Architect and implement scalable, secure infrastructure for AI and ML workloads.
• Build and maintain model-focused CI/CD pipelines spanning data ingestion, deployment, serving, and monitoring.
• Partner with AI researchers and software engineers to improve system performance and streamline experimentation and delivery.
• Guide platform development and deployment practices, and mentor less experienced engineers.
• Maintain the reliability, security, and performance of AI systems.
• Track relevant developments and assess new approaches for the platform.

Skills

Leadership experience

DevOps

ML infra

Platform engineering

Cloud services

Collaboration

Tools

Docker

Kubernetes

Kubeflow

MLflow

SageMaker

Terraform

Ansible

GitHub Actions

GitLab CI/CD

Jenkins

Job description

Role overview

Lead the design and operation of infrastructure that supports AI and machine learning capabilities in a scientific software platform. This senior role connects research and software engineering teams, making it possible to build, test, deploy, and monitor models reliably at scale. The work centers on secure, resilient infrastructure, automation, and a smooth path from experimentation to production.

Responsibilities

• Architect and implement scalable, secure infrastructure for AI and ML workloads.
• Build and maintain model-focused CI/CD pipelines spanning data ingestion, deployment, serving, and monitoring.
• Partner with AI researchers and software engineers to improve system performance and streamline experimentation and delivery.
• Guide platform development and deployment practices, and mentor less experienced engineers.
• Maintain the reliability, security, and performance of AI systems.
• Track relevant developments and assess new approaches for the platform.

Requirements

• At least five years in DevOps, ML infrastructure, or platform engineering, including senior or leadership experience.
• Deep experience with a major cloud provider and its AI/ML and container services.
• Hands‑on experience with ML orchestration platforms such as Kubeflow, MLflow, or SageMaker.
• Strong Docker and Kubernetes expertise for operating and scaling AI/ML workloads.
• Strong automation skills in Python, Go, or Bash.

Nice to have

• Infrastructure provisioning experience with Terraform or Ansible.
• Experience building automated CI/CD pipelines with tools such as GitHub Actions, GitLab CI/CD, or Jenkins.
• Strong communication and collaboration skills across technical and business teams.

Benefits and work setup

• Remote candidates must be based in Canada; working hours align with Eastern Time.
• The stated base salary range is CAD $130,000–$165,000. Actual pay depends on factors including skills, experience, education, and work location.