AI Ops

Job Description

Job Location: Chennai, India

Job Title: DevOps Engineer II (AI Ops / ML Ops)

Work Mode: Onsite

Our Department: Trimble's Construction Management Solutions (CMS) division is dedicated to transforming the construction industry. We provide technology solutions that streamline and optimize workflows for preconstruction, project management, and field operations. By connecting the physical and digital worlds, we help our customers improve productivity, efficiency, and project outcomes.

Are you passionate about deploying, monitoring, and scaling machine learning systems in production environments and eager to contribute to robust AI infrastructure within a collaborative team

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 direct guidance from experienced professionals.

- 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:

- 2 to 5 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.

- Experience with Microsoft Azure and its services including ML/AI (Azure ML, Azure DevOps, etc.) Must Have

- Foundational knowledge of DevOps principles and practices, with understanding of CI/CD concepts and basic system administration.

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

- Understanding of containerization technologies (Docker) and basic orchestration concepts (Kubernetes fundamentals).

- Familiarity with version control systems (Git) and collaborative development workflows.

- Basic understanding of machine learning concepts and the ML model lifecycle from development to production.

Preferred:

- Familiarity with MLOps tools and frameworks (MLflow, Kubeflow, DVC, or similar).

- Basic experience with monitoring and observability tools (Prometheus, Grafana, ELK stack).

- Understanding of Infrastructure as Code (IaC) tools like Terraform or Ansible.

- Experience with Windows/Linux system administration and command-line tools.

- Knowledge of database systems and data pipeline technologies.

- Exposure to model serving frameworks (TensorFlow Serving, TorchServe, ONNX Runtime).

- Basic understanding of security best practices for ML systems and data governance.

About Our Division: Construction Management Solutions (CMS)

Trimble's Construction Management Solutions (CMS) division is dedicated to transforming the construction industry. We provide technology solutions that streamline and optimize workflows for preconstruction, project management, and field operations. By connecting the physical and digital worlds, we help our customers improve productivity, efficiency, and project outcomes.