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 pipelinesAdminister and automate AWS and GCP cloud environmentsBuild and manage infrastructure using Infrastructure as CodeWork closely with software developers on deployments and production releasesAutomate infrastructure, operational processes and development workflowsManage cloud networking, including VPCs, subnets, load balancers, WAF and DNSSupport IAM, secrets management and least-privilege securityMonitor and improve the availability and performance of production applicationsParticipate in code reviews, testing and Agile deliveryEvaluate and implement new technologies, including AI tools and agentsMentor junior team members and promote DevOps best practicesWhat We’re Looking For 5+ years of DevOps / Infrastructure Engineering experience5+ years working with AWS and/or GCPStrong Linux/UNIX administrationStrong Infrastructure as Code experienceHands-on CI/CD experience with tools such as Jenkins or GCP Cloud BuildStrong cloud networking knowledgeExperience with IAM, secrets management and cloud securityExperience with monitoring tools such as AWS CloudWatch or GCP MonitoringStrong scripting skills with Python and/or BashExperience with GitHub, SonarQube or similar development lifecycle toolsExperience working closely with software development teamsUnderstanding of security and compliance best practicesExperience with modern AI development tools such as Copilot, Claude Code or similarBachelor's degree in Software Engineering or a related technical field Nice to Have Experience with security tools such as GuardDuty, AWS Config, CrowdStrike or TaniumExposure to MLOps, AI/ML infrastructure, model deployment or ML pipelinesKnowledge 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.