Machine Learning Engineer

Toronto, ON
Hybrid
Posted Oct 10, 2026
1 position

$115,000–$120,000 / year

Opens LinkedIn

Employment type: Full-time
Experience level: Senior · 5+ years
Minimum education: Bachelor’s degree
Posting language: English
Working hours: 40 hours per week
Office presence: 2 days per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

Own and improve CI/CD pipelines, automate and administer AWS and GCP infrastructure, and support secure, reliable production deployments. Collaborate with development teams on releases, monitoring, code reviews, and Agile delivery while evaluating AI tools and mentoring junior team members.

Job details

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.

What you’ll do

Requirements

Requires 5+ years of DevOps or infrastructure engineering experience, strong AWS and/or GCP expertise, Linux administration, Infrastructure as Code, CI/CD, cloud networking, security, monitoring, and Python and/or Bash scripting. Candidates should also have experience working with software development teams and modern AI development tools; a bachelor's degree in Software Engineering or a related technical field is listed.