Machine Learning Engineer

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
• Strong 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 great opportunity for someone who enjoys automation, cloud infrastructure, DevOps and AI/ML technologies and wants to work closely with development teams in a collaborative environment.