← All Roles
AI and Machine Learning

Senior Machine Learning Engineer, Azure MLOps

Design and operate end-to-end ML pipelines on Azure at enterprise scale. Own the MLOps infrastructure, from CI/CD pipelines and containerised model deployment to cost governance and cross-team technical liaison.

Apply for This Role All Open Roles

About This Role

A senior engineering role for an ML practitioner who is as strong on operations and deployment as they are on modelling. You will own the production reliability of ML systems, build reusable pipeline frameworks, and work as the technical bridge between data science, DevOps, and IT teams.

What You Will Do

  • Design and manage end-to-end ML pipelines using Azure ML, Databricks, and PySpark for large-scale data processing and model training
  • Build and maintain automated CI/CD pipelines using GitHub Actions with SonarQube integration for code quality and security
  • Develop reusable, modular ML pipeline templates to drive deployment efficiency across the enterprise
  • Containerise and deploy ML models using Azure Kubernetes Service (AKS) and Docker, ensuring high availability and auto-scaling
  • Design and manage secure APIs for ML model interaction with downstream applications
  • Perform model lifecycle management, optimisation, data drift monitoring, and automated data refresh checks
  • Implement cost-monitoring strategies for high-compute training and deployment phases
  • Maintain detailed technical documentation for workflows, pipeline templates, and optimisation strategies
  • Act as the technical liaison between Data Scientists, DevOps, and IT teams across Dev, QA, and Production environments

What You Need to Succeed

  • Bachelor's degree in Engineering, Computer Science, or related field
  • 5+ years of experience with deep focus on the Azure MLOps toolstack
  • Proven track record of deploying and maintaining ML models in high-scale production environments
  • Hands-on expertise with Azure Machine Learning and Databricks
  • Strong command of Kubernetes (AKS) and API-based deployment platforms
  • Solid grasp of DevOps practices and containerisation with Docker
  • Experience with code quality automation tools including SonarQube
  • Exceptional problem-solving skills with the ability to operate in a fast-paced collaborative environment

What Will Give You an Edge

  • Familiarity with broader solution architecture principles
  • Azure certifications: AI-900, DP-100, or AZ-305
  • Experience with PySpark and large-scale distributed data processing

What Qfyre Offers

  • Placement in a high-impact MLOps role within an enterprise AI programme
  • Genuine ownership of production ML infrastructure, not a support role
  • Market-competitive compensation with flexibility on hybrid working
  • Exposure to cutting-edge Azure AI toolstack at scale

Skills and Technologies

Azure MLMLOpsDatabricksAKSCI/CDAI
Apply

Apply for Senior Machine Learning Engineer, Azure MLOps

Complete the form below. Our team reviews every application personally, no automated filtering, no keyword matching. We will be in touch within two business days.

Drag and drop or browse to upload

PDF, DOC, or DOCX, max 5MB

Your application is reviewed by a domain expert, not an ATS. We do not share your details without your consent. See our Privacy Policy.

FAQ

Questions About This Role

Common questions from candidates and applicants.

What does the application process look like for the Senior Machine Learning Engineer, Azure MLOps role?+

Submit your application via the form on this page. A Qfyre domain specialist will review your profile, not an automated keyword filter, and will be in touch within two business days if there is a strong fit. We may arrange a brief introductory call before presenting your profile to the client.

Is this Senior Machine Learning Engineer, Azure MLOps role a permanent position or contract?+

This is a Full Time position based in Bengaluru / Hyderabad. The working mode is Hybrid. Specific contract terms and benefits are discussed during the briefing process once your profile has been reviewed.

What experience level is required for the Senior Machine Learning Engineer, Azure MLOps role?+

This role requires 5+ years of relevant experience. The specific technical requirements and domain expectations are outlined in the full job description above. If your experience is slightly outside the stated range but you have strong relevant capability, we encourage you to apply, we assess profiles holistically, not against a checklist.

Does Qfyre assist with relocation for this role?+

Relocation support varies by client and mandate. Mention your relocation preferences in the application form and our team will clarify the client's position during the initial briefing. Most of our GCC and enterprise clients have structured relocation support programmes for senior hires.