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

Revvity Health Sciences; Canada; Remote; CAD 130,000 - 165,000; Full time

Benefits offered by this job

Remote work

Competitive salary

Job summary

Revvity is seeking a Principal DevOps Engineer (AI/ML Infrastructure) to design, build and operate scalable AI platforms in a remote Canada context. You will bridge AI researchers and software teams to reliably develop and deploy models at scale.

This senior role focuses on automation, CI/CD for AI workloads, security, and performance. You will mentor engineers, implement cloud-native tooling (Kubeflow, MLflow, SageMaker), and collaborate across R&D to advance the Signals platform.

Qualifications

• 5+ years in DevOps, ML infrastructure, or platform engineering, in a senior or leadership role.
• 5+ years hands-on with AWS, Azure, or GCP including AI/ML services.
• 5+ years experience with ML orchestration and platform tools (Kubeflow, MLflow, SageMaker).
• 5+ years deep expertise with Docker and Kubernetes for AI workloads.
• 5-8+ years coding in Python, Go or Bash for automation.

Responsibilities

• Architect, design, and lead the implementation of scalable, secure, and resilient infrastructure for AI/ML workloads.
• Build and maintain CI/CD pipelines for AI models, managing data ingestion to model serving and monitoring.
• Mentor junior engineers and drive best practices for AI/ML platform development, code management, and deployment.
• Collaborate with AI researchers and software engineers to optimize performance and streamline end-to-end development and experimentation.

Skills

DevOps

ML Infrastructure

Platform Engineering

Python

Docker

Kubernetes

Go

Automation

Tools

Kubeflow

MLflow

SageMaker

Terraform

Ansible

GitHub Actions

GitLab CI/CD

Jenkins

Job description

Job Title

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

Location(s)

CAD Remote - ON

About Us

Revvity is a developer and provider of end-to-end solutions designed to help scientists, researchers, and clinicians solve the world's greatest health challenges. We pair the enthusiasm of an industry disruptor with the experience of a longtime leader. Our team of 11,000+ colleagues from around the globe are vital to our success and the reason we're able to push boundaries in pursuit of better human health.

Find your future at Revvity

Revvity Signals makes market-leading software that empowers scientists across Life Science R&D, clinical research, and specialty chemicals to make better medicines and products, faster. Our flagship offering is the SaaS Signals Research Platform that provides knowledge capture, collaboration, analysis and visualization tools across the full depth and breadth of scientific discovery workflows. The viral adoption of our software is accelerating innovation, expediting drug development for a healthier world and facilitating the creation of sustainable materials.

Join us as a Principal DevOps Engineer (AI/ML Infrastructure) , where you'll play a pivotal role building out, maintaining and operating our AI infrastructure, that is part of the Signals Platform. This is your chance to work closely with a dedicated team of experience developers building out AI capabilities within our product.

We are seeking a senior-level technical expert working within the R&D organization, who integrates and orchestrates the entire lifecycle of artificial intelligence (AI) and machine learning (ML) projects.

You will be responsible for bridging the gap between AI researchers, and traditional software development teams to ensure AI models are reliably built, tested, and deployed into production at scale.

This role requires a blend of deep expertise in DevOps principles, software engineering, and AI/ML infrastructure, with a strong focus on automation, scalability, and security.

Main functions

• Architect, design, and lead the implementation of scalable, secure, and resilient infrastructure for AI/ML workloads
• Build and maintain the continuous integration and continuous deployment (CI/CD) pipelines specifically for AI models, managing everything from data ingestion to model serving and monitoring
• Act as a subject matter expert and mentor for junior engineers, driving the adoption of best practices for AI/ML platform development, code management, and deployment
• Work closely with AI researchers, and software engineers to optimize performance and streamline the end-to-end development and experimentation process.
• Ensure the reliability, security, and performance of AI systems.
• Stay ahead of industry trends and bring innovative AI solutions to the table.

Basic Qualifications

• 5+ years of experience in DevOps, ML Infrastructure, or Platform Engineering, with several years in a senior or leadership capacity.
• 5+ years of deep, expert-level knowledge of at least one major cloud provider (e.g., AWS, Azure, or GCP), including their AI/ML and containerization services.
• 5+ years of hands-on experience with ML orchestration and platform tools like Kubeflow, MLflow, or Amazon SageMaker.
• 5-8+ years of deep expertise with Docker and Kubernetes for managing and scaling AI/ML workloads.
• 5-8+ years strong coding skills in languages such as Python, Go, or Bash for automation.

Preferred Qualifications

• Proficiency with tools like Terraform or Ansible to manage and provision infrastructure.
• Experience building robust and automated CI/CD pipelines using tools like GitHub Actions, GitLab CI/CD, or Jenkins.
• Excellent collaboration and communication skills to work effectively with cross-functional technical and business teams.

The working hours for this position will be EST. 'Remote Canada' Candidates, only.

Please include a 'valid LinkedIn profile' and added work links, to your resume.

The base salary range for this full-time position is $130,000 - $165,000 CAD . This range reflects the minimum and maximum target for a new hire in this position. The base pay actually offered to the successful candidate will take into account internal equity, work location, and additional factors, including job-related skills, experience, and relevant education or training. This range allows for the successful candidate to have an opportunity to progress within the position and develop at our company. This compensation range does not take into account other benefits which may be applicable and are dependent on the level and position offe