DevOps Engineer (MLOps)

TL;DR

DevOps Engineer (MLOps): Building and scaling cloud infrastructure and MLOps pipelines for an AI-powered influencer marketing platform with an accent on Kubernetes, AWS, and ML deployment. Focus on automating training pipelines, managing GPU-enabled workloads, and improving CI/CD for model experimentation and production.

Location: Hybrid in Vancouver, BC, Canada

Salary: $120,000 - 140,000 CAD

Company

hirify.global is an AI-powered influencer marketing company that provides brands with intelligence and guidance to create data-driven campaigns.

What you will do

• Build and manage infrastructure to deploy ML models into production using CI/CD pipelines, Flask-based APIs, and orchestration tools like Airflow or Kubeflow.
• Automate training pipelines, model registries, validation, and deployment strategies using Amazon SageMaker.
• Monitor model performance, latency, data drift, and resource usage using Prometheus, Grafana, and Amazon CloudWatch.
• Design and maintain scalable cloud infrastructure as code using Terraform across AWS and GCP.
• Collaborate with Data Scientists and Product Engineers to streamline GitOps practices and end-to-end ML workflows.
• Contribute to platform standards for infrastructure, CI/CD, and data pipelines to enhance system reliability and developer experience.

Requirements

• 2–5 years of hands-on DevOps or cloud engineering experience in production environments.
• Expertise with Kubernetes (EKS), Helm, and microservices.
• 1-2 years of experience with AWS, SageMaker, and creating data pipelines.
• 1-2 years of experience with LLM deployments on Kubernetes and managing GPU-enabled nodes.
• Proven track record using Terraform for scalable Infrastructure as Code.
• Must be located in or able to work from Vancouver, BC

Culture & Benefits

• Market-based and data-driven compensation approach with bi-annual evaluations.
• Eligibility for comprehensive benefits plans for all permanent team members.
• Inclusive work environment focusing on culture add rather than culture fit.
• Flexible hybrid work model with established office hubs.
• Strong emphasis on automation, continuous improvement, and operational excellence.