Azure DevOps Engineer/ MLOps

• Posted 7 days ago • Updated 10 hours ago
Full Time
On-site
$112000 - $130000/yr
Fitment

Dice Job Match Score™

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Job Details

Skills

  • DevOps
  • Digital Marketing
  • Customer Facing
  • Orchestration
  • Data Science
  • Artificial Intelligence
  • Computer Networking
  • Storage
  • Terraform
  • Machine Learning Operations (ML Ops)
  • Machine Learning (ML)
  • Lifecycle Management
  • Databricks
  • Microsoft Azure
  • Continuous Integration
  • Continuous Delivery
  • Kubernetes
  • Cloud Computing
  • Generative Artificial Intelligence (AI)
  • Workflow
  • DevSecOps
  • Identity Management
  • Collaboration
  • SAP BASIS
  • Recruiting
  • Access Control

Summary

This is a senior-level opportunity to lead the design and evolution of a cloud-native platform within a fast-moving organization operating in the communications and digital advertising space.

Built on Microsoft Azure, the platform underpins data-intensive, customer-facing systems, with a strong emphasis on enabling MLOps and AI-driven workloads using Databricks. You will architect and operate scalable infrastructure that supports both high-throughput application services and advanced machine learning pipelines, ensuring reliable deployment, monitoring, and lifecycle management of models in production.

The role blends deep Azure platform engineering expertise with hands-on ownership of CI/CD, infrastructure as code, and container orchestration, while partnering closely with data science and product teams to operationalize ML solutions that drive campaign performance and audience insights. This is a high-impact position with significant influence over platform standards, automation strategy, and the integration of AI capabilities into core systems.

Required Skills & Experience
  • Strong hands-on experience with Microsoft Azure, including core services across compute, networking, and storage, alongside Infrastructure as Code (Terraform or equivalent)
  • Proven background in MLOps practices, particularly supporting ML pipelines and model lifecycle management using Databricks and Azure-native tooling
  • Deep expertise in CI/CD pipelines, Kubernetes, and containerized environments, with experience running production-grade distributed systems at scale

Desired Skills & Experience
  • Experience implementing observability frameworks (monitoring, logging, alerting) and defining SLIs/SLOs in cloud environments
  • Exposure to Generative AI or LLM-based systems, including inference workflows or retrieval-augmented architectures
  • Familiarity with DevSecOps practices, including identity management, secrets handling, and zero-trust security models

Daily Responsibilities
  • Hands-On Engineering: 65%
  • Team Collaboration & Cross-Functional Work: 35%

    Applicants must be currently authorized to work in Canada on a full-time basis now and in the future.

    Accommodation will be provided in all parts of the hiring process as required under Motion Recruitment's Employment Accommodation policy. Applicants need to make their needs known in advance.

    #LI-AC1
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10105282
  • Position Id: 870150
  • Posted 7 days ago
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