Lead/ Staff DevOps Engineer - (AI / ML Ops)

Job Location: Chennai, India

Job Title: Lead / Staff DevOps Engineer (AI Ops / ML Ops)

Work Mode: Onsite

Experience Level: Openings in Multiple Levels

(https://forms.gle/KkUkJscs7D4VjrYKA).

What You Will Do

This role offers an exciting opportunity to work in AI/ML Development and Operations (DevOps) engineering, working within a dynamic team that values reliability and continuous improvement. The successful candidate will contribute to the deployment and maintenance of AI/ML systems in production, gaining hands-on experience with MLOps best practices and infrastructure automation. This position provides a structured environment for developing core competencies in ML system operations, DevOps practices, and production ML monitoring, with guidance from Technical Leadership team.

• Assist in the deployment and maintenance of machine learning models in production environments under direct supervision, learning containerization technologies like Docker and Kubernetes.
• Support CI/CD pipeline development for ML workflows, including model versioning, automated testing, and deployment processes using tools like Azure DevOps.
• Monitor ML model performance, data drift, and system health in production environments, implementing basic alerting and logging solutions.
• Contribute to infrastructure automation and configuration management for ML systems, learning Infrastructure as Code (IaC) practices with tools like Terraform or CloudFormation.
• Collaborate with ML engineers and data scientists to operationalize models, ensuring scalability, reliability, and adherence to established MLOps procedures and best practices.

What Skills & Experience You Should Bring (Required):

• 6 to 14 Years

  of professional experience in in DevOps, MLOps, or systems engineering environment.
• Bachelor's degree in Computer Science, Engineering, Information Technology, or a closely related technical field. Trimble's Professional ladder typically requires four or more years of formal education.
• Expert level experience in working with

  Microsoft Azure

  and its services including ML/AI (Azure ML, Azure DevOps, etc.) with exposure to

  Design

  ,

  development

  , and/or

  implementation

  of cloud

  architectures,

  including the front-end platforms, storage, networks, and servers needed for the cloud infrastructure. -

  Must Have

• Highly proficient in

  Python

  or other scripting languages (Shell / Bash / PowerShell / Perl) for automation scripting and system integration -

  Must have

• Strong experience of containerization technolog(

  Docker

  ) and orchestration concepts (

  Kubernetes

  ).
• Strong experience of DevOps principles and practices, with handson working experience in of CI/CD and system administration.
• Strong experience with

  CI/CD

  tools such as Jenkins, GitHub Actions, or ArgoCD.
• Experience with monitoring and observability tools (Prometheus, Grafana, Datadog, New Relic).
• Hands-on with version control systems (Git) and collaborative development workflows.
• Experience with data engineering concepts and technologies (SQL, NoSQL, ETL pipelines).
• Experience with MLOps tools and frameworks (Kubeflow, MLflow, Weights & Biases, or similar).

Preferred:

• Experience with other cloud platforms (GCP, AWS) is a plus.
• Hands-on experience in machine learning concepts and the ML model lifecycle from development to production.
• Experience of AIOps and incident management platforms like Moogsoft, BigPanda, PagerDuty, or Opsgenie.
• Working knowledge with model serving frameworks (TensorFlow Serving, TorchServe, ONNX Runtime).
• Working knowledge of security best practices for ML systems and data governance.

  Role & responsibilities