AI/ML Infrastructure Engineer

AI/ML Infrastructure Engineer

Canada(Remote)

Full-time (Permanent)

JD:

We are looking to hire an Skilled AI/ML Infrastructure Engineer immediately

Role Overview:

We are looking for an experienced Infrastructure Engineer to design, automate, and operate scalable cloud infrastructure supporting data platforms and AI/ML workloads across GCP and Azure. This role focuses on Infrastructure such as Code, CI/CD automation, cloud networking, and enabling reliable, secure environments for data engineering and analytics teams.

Key Responsibilities:

• Design, provision, and manage cloud infrastructure using Terraform
• Build and maintain CI/CD pipelines using Azure DevOps
• Provision and manage GCP infrastructure, including compute, storage, IAM, and networking
• Support and manage Azure infrastructure (VNets, networking, compute, storage)
• Design and implement network provisioning (VPC/VNet architecture, routing, firewalls, load balancers, private connectivity)
• Build and operate infrastructure for data platforms (data lakes, warehouses, streaming, analytics platforms)
• Provision and support AI/ML infrastructure, including GPU resources and AI platforms
• Implement security best practices, IAM, encryption, and compliance controls
• Optimize infrastructure for performance, reliability, and cost
• Collaborate with data engineering, analytics, and ML teams
• Document infrastructure, architecture, standards, and operational runbooks

Required Skills & Qualifications:

• Strong experience with Terraform (Infrastructure as Code)
• Experience with CI/CD pipelines, preferably Azure DevOps
• Strong hands on experience with Google Cloud Platform (GCP)
• Solid understanding of cloud networking and network provisioning
• Experience supporting data platforms or large scale data workloads
• Experience with AI/ML infrastructure
• Strong Linux and scripting skills (Bash, Python, etc.)

Preferred / Nice to Have:

• Hands on experience with Azure infrastructure
• Experience with Kubernetes (GKE / AKS)
• Experience with data services such as BigQuery, Dataflow, Dataproc, Synapse, ADLS, Snowflake
• Monitoring and observability tools (Prometheus, Grafana, Cloud Monitoring)
• Multi cloud experience and relevant certifications