AI/ML Platform Engineer (Azure & GCP)

IT Accel, Inc.; Toronto; Hybrid; CAD 140,000 - 180,000; Full time

Job summary

IT Accel, Inc. is seeking an experienced AI/ML Platform Engineer to design and deliver enterprise-scale AI/ML solutions on Azure and GCP. This hybrid Toronto role focuses on enabling AI/ML capabilities across the organization, helping teams build, deploy, and scale intelligent solutions securely and efficiently.

You will collaborate with cloud, security, and engineering teams to build robust platforms, automate AI/ML workflows, and ensure compliance with enterprise standards.

Qualifications

• 3+ years experience as an AI/ML Platform Engineer or similar role.
• Strong experience with Azure (preferred) and/or GCP cloud platforms.
• Proficiency in Python, APIs, and automation scripting.
• Hands-on experience with Terraform, CI/CD pipelines, and GitHub Actions.
• Experience with MLOps/AIOps practices and model lifecycle management.
• Knowledge of Generative AI, RAG architectures, and LLM frameworks (e.g., LangChain, Semantic Kernel).
• Understanding of AI ecosystem tools (evaluation, monitoring, vector databases, governance).
• Experience integrating AI/ML services into enterprise applications.
• Strong understanding of cloud security, RBAC, and data protection principles.

Responsibilities

• Design and implement scalable AI/ML platforms and services on Azure (and GCP).
• Enable and support Generative AI and ML use cases across the business.
• Build and maintain MLOps pipelines for model training, deployment, and monitoring.
• Develop infrastructure as code using Terraform and CI/CD pipelines (GitHub Actions).
• Integrate AI/ML services with enterprise systems via APIs and webhooks.
• Ensure secure deployment of data and models, following cloud security and compliance standards.
• Collaborate with cross-functional teams (cloud, security, risk, development).
• Troubleshoot cloud infrastructure, networking, and performance issues.
• Support automation of AI/ML services and platform capabilities.
• Contribute to DevOps practices within an Agile environment.

Skills

AI/ML Platform Engineering

Azure/GCP cloud

Python

APIs & automation

Terraform

CI/CD (GitHub Actions)

MLOps/AIOps

Generative AI / LLM

Cloud security & RBAC

Problem solving & communication

Tools

Terraform

GitHub Actions

Job description

Contract-to-Hire | Hybrid Toronto, CA

We are seeking an experienced AI/ML Platform Engineer to design and deliver enterprise-scale AI and machine learning solutions on Azure and GCP. This role focuses on enabling AI/ML capabilities across the organization, helping teams build, deploy, and scale intelligent solutions securely and efficiently.

You will work closely with cloud, security, and engineering teams to build robust platforms, automate AI/ML workflows, and ensure compliance with enterprise standards.

Key Responsibilities

• Design and implement scalable AI/ML platforms and services on Azure (and GCP)
• Enable and support Generative AI and ML use cases across the business
• Build and maintain MLOps pipelines for model training, deployment, and monitoring
• Develop infrastructure as code using Terraform and CI/CD pipelines (GitHub Actions)
• Integrate AI/ML services with enterprise systems via APIs and webhooks
• Ensure secure deployment of data and models, following cloud security and compliance standards
• Collaborate with cross-functional teams (cloud, security, risk, development)
• Troubleshoot cloud infrastructure, networking, and performance issues
• Support automation of AI/ML services and platform capabilities
• Contribute to DevOps practices within an Agile environment

Required Skills & Experience

• 3+ years experience as an AI/ML Platform Engineer or similar role
• Strong experience with Azure (preferred) and/or GCP cloud platforms
• Proficiency in Python, APIs, and automation scripting
• Hands-on experience with Terraform, CI/CD pipelines, and GitHub Actions
• Experience with MLOps/AIOps practices and model lifecycle management
• Knowledge of Generative AI, RAG architectures, and LLM frameworks (e.g., LangChain, Semantic Kernel)
• Understanding of AI ecosystem tools (evaluation, monitoring, vector databases, governance)
• Experience integrating AI/ML services into enterprise applications
• Strong understanding of cloud security, RBAC, and data protection principles
• Ability to troubleshoot Azure networking (DNS, connectivity, routing)
• Strong analytical, problem-solving, and communication skills

Nice to Have

• Experience in financial services or regulated environments
• Familiarity with agentic AI platforms or Copilot ecosystems
• Knowledge of PKI and certificate management in cloud environments

What We’re Looking For

• A self-starter who can work independently and in a team
• Strong critical thinking and problem-solving abilities
• Passion for AI/ML and continuous learning