Site Reliability Engineer (SRE) | AI Ops / MLOps | Cloud & DevOps

Company: Trimble – Construction Management Solutions (CMS)
Location: Chennai, India
Work Mode: Onsite
Employment Type: Full-Time
Experience: 1 – 2 Years

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Trimble's CMS division is dedicated to transforming the construction industry with cloud technology, AI/ML systems, and DevOps automation. By connecting the physical and digital worlds, Trimble enables customers to streamline workflows, improve project productivity, and enhance operational efficiency.

As a Site Reliability Engineer (AI Ops / MLOps), you will help deploy, monitor, and scale machine learning systems, ensuring high-availability, performance, and reliability across production ML environments. This is an excellent opportunity for professionals looking to grow in MLOps, cloud automation, DevOps engineering, and enterprise infrastructure reliability.

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What You Will Do

• Assist in deploying and maintaining machine learning models in production environments, learning Docker containerization and Kubernetes orchestration
• Build and support CI/CD pipelines for ML workflows including model versioning, automated testing, and deployments using Azure DevOps
• Monitor ML model performance, system health, and data drift, implementing alerting and observability using Prometheus, Grafana, ELK Stack
• Contribute to infrastructure automation and configuration management for ML systems using Terraform, CloudFormation, or Ansible
• Collaborate with ML engineers, data scientists, and DevOps teams to operationalize models for scalability, reliability, and enterprise-grade performance
• Implement IaC practices to provision cloud infrastructure and manage production ML environments
• Support troubleshooting, incident response, and cloud system performance optimization
• Learn and implement MLOps best practices, CI/CD automation, and production-ready cloud security and compliance standards
• Contribute to AI/ML infrastructure design, focusing on high-availability systems, container orchestration, and enterprise cloud automation

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Required Skills & Experience

• 1–2 years professional experience in DevOps, MLOps, or systems engineering
• Bachelor’s degree in Computer Science, IT, or Engineering
• Hands-on experience with Microsoft Azure Cloud Services, including Azure ML, Azure DevOps, and cloud resource management
• Understanding of DevOps principles, CI/CD concepts, and system administration
• Proficiency in Python, Bash, Shell, or PowerShell scripting for automation and integration
• Familiarity with Docker containerization, Kubernetes fundamentals, and Git workflows
• Basic knowledge of machine learning concepts, model lifecycle, and production ML monitoring

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Preferred Skills

• Familiarity with MLOps frameworks such as MLflow, Kubeflow, or DVC
• Experience with observability, logging, and monitoring tools like Prometheus, Grafana, or ELK Stack
• Understanding of Infrastructure as Code (IaC) and cloud automation practices
• Exposure to Windows/Linux system administration and command-line tools
• Knowledge of databases, data pipelines, and cloud-native storage solutions
• Experience with model serving frameworks such as TensorFlow Serving, TorchServe, or ONNX Runtime
• Awareness of cloud security best practices, compliance standards, and data governance

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Why Join Trimble?

• Work on enterprise-grade AI/ML systems, cloud infrastructure, and DevOps automation
• Gain hands-on experience in Azure Cloud Engineering, Kubernetes administration, Docker orchestration, Terraform infrastructure automation, and CI/CD pipeline engineering
• Collaborate with multi-functional teams and global experts in AI Ops, MLOps, and site reliability engineering
• Learn and implement production-ready observability, monitoring, and automation strategies for high-availability cloud systems
• Opportunity to grow in a fast-paced, innovation-driven, and technology-first environment

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Benefits

• Exposure to cutting-edge cloud platforms, AI/ML infrastructure, and enterprise DevOps
• Hands-on experience with high-value technologies like Azure, Terraform, Kubernetes, Docker, Prometheus, Grafana, ELK Stack, CI/CD automation, and cloud security monitoring
• Mentorship and guidance from senior SRE and DevOps professionals
• Opportunity to contribute to enterprise cloud solutions and AI-driven operations
• Career growth in Site Reliability Engineering, Cloud DevOps, and MLOps

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How to Apply

Apply using below link