AI and Machine Learning Systems Engineer

1 day ago

Chennai, Tamil Nadu, India beBeeDevOps Full time ₹ 20,00,000 - ₹ 32,00,000
DevOps Engineer for AI/ML Infrastructure

We are seeking a highly skilled DevOps engineer to contribute to the development and operation of our robust AI infrastructure. This role offers an exciting opportunity to work in AI/ML development and operations engineering within a dynamic team that values reliability and continuous improvement.

The ideal candidate will have experience with Microsoft Azure, Python or other scripting languages, containerization technologies (Docker), basic orchestration concepts (Kubernetes fundamentals), version control systems (Git), collaborative development workflows, and basic understanding of machine learning concepts and the ML model lifecycle.

This position requires a structured environment for developing core competencies in ML system operations, DevOps practices, and production ML monitoring. The successful candidate will assist in deploying and maintaining machine learning models in production environments, gaining hands-on experience with MLOps best practices and infrastructure automation.

  • Assist in the deployment and maintenance of machine learning models in production environments under direct supervision.
  • Support CI/CD pipeline development for ML workflows, including model versioning, automated testing, and deployment processes.
  • Monitor ML model performance, data drift, and system health in production environments.
  • Contribute to infrastructure automation and configuration management for ML systems.
  • Collaborate with ML engineers and data scientists to operationalize models.
Key Skills:
  • Microsoft Azure
  • Python
  • Docker
  • Kubernetes
  • Git
  • Collaborative development workflows
  • MLOps best practices
  • Infrastructure automation
Becoming a part of our team means:
  • Gaining hands-on experience with ML system operations, DevOps practices, and production ML monitoring
  • Developing core competencies in ML system operations, DevOps practices, and production ML monitoring
  • Contributing to the development and operation of our robust AI infrastructure

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