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 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.

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