MLOps Developer / DevOps Infrastructure Engineer

Location: Toronto, ON – Hybrid, minimum 2 days onsite per week, with the possibility of 3 days

Employment Type: Permanent, Full-Time

Salary: $115,000–$120,000

We are looking for an experienced MLOps / DevOps Infrastructure Engineer with strong cloud, automation and software delivery experience. This role combines hands-on AWS/GCP infrastructure, CI/CD and DevOps with exposure to AI/ML technologies and modern AI development tools.

What You’ll Do
Own and improve CI/CD, build and deployment pipelines
Administer and automate AWS and GCP cloud environments
Build and manage infrastructure using Infrastructure as Code
Work closely with software developers on deployments and production releases
Automate infrastructure, operational processes and development workflows
Manage cloud networking, including VPCs, subnets, load balancers, WAF and DNS
Support IAM, secrets management and least-privilege security
Monitor and improve the availability and performance of production applications
Participate in code reviews, testing and Agile delivery
Evaluate and implement new technologies, including AI tools and agents
Mentor junior team members and promote DevOps best practices

What We’re Looking For




5+ years of DevOps / Infrastructure Engineering experience
5+ years working with AWS and/or GCP
Strong Linux/UNIX administration
Solid Infrastructure as Code experience
Hands-on CI/CD experience with tools such as Jenkins or GCP Cloud Build
Strong cloud networking knowledge
Experience with IAM, secrets management and cloud security
Experience with monitoring tools such as AWS CloudWatch or GCP Monitoring
Strong scripting skills with Python and/or Bash
Experience with GitHub, SonarQube or similar development lifecycle tools
Experience working closely with software development teams
Understanding of security and compliance best practices
Experience with modern AI development tools such as Copilot, Claude Code or similar
Bachelor's degree in Software Engineering or a related technical field

Nice to Have
Experience with security tools such as GuardDuty, AWS Config, CrowdStrike or Tanium
Exposure to MLOps, AI/ML infrastructure, model deployment or ML pipelines
Knowledge of Generative AI, Transformers or Vision-Language Models (VLMs)

This is a excellent chance for someone who enjoys automation, cloud infrastructure, DevOps and AI/ML technologies and wants to work closely with development teams in a collaborative setting.

📌 Machine Learning Engineer Toronto
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📍 Toronto