Mlops

Company Description IITM Pravartak Technologies Foundation is a Technology Innovation Hub (TIH) hosted at IIT Madras under the Department of Science and Technology’s National Mission on Interdisciplinary Cyber-Physical Systems. The hub focuses on Sensor, Networking, Actuators, and Control Systems (SNACS), enabling cutting-edge research and industry collaboration in these domains. It provides a dynamic environment where academic experts, industry partners, and innovators work together to build scalable, real-world solutions. Team members gain exposure to advanced technologies, interdisciplinary projects, and opportunities to contribute to national mission-driven initiatives.

Role Description This is a full-time, on-site MLOps role based in Chennai. The MLOps professional will design, implement, and maintain production-grade machine learning pipelines, including data ingestion, model training, deployment, and monitoring. Day-to-day responsibilities include building and managing CI/CD workflows for ML models, optimizing infrastructure for performance and cost, and ensuring reliability, security, and scalability of ML services. The role involves close collaboration with data scientists, software engineers, and domain experts to operationalize models, maintain documentation, and support continuous improvement of deployed solutions.

Qualifications

• Strong understanding of MLOps principles, including ML lifecycle management, CI/CD for ML, and model monitoring.
• Hands-on experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization/orchestration tools (e.g., Docker, Kubernetes).
• Proficiency in scripting or programming languages commonly used in ML and DevOps (e.g., Python, Bash) and version control (e.g., Git).
• Knowledge of ML frameworks and tooling (e.g., TensorFlow, PyTorch, scikit-learn, MLflow, Kubeflow, Airflow) for model development and deployment.
• Experience with data pipelines, ETL processes, and monitoring/observability tools (e.g., Prometheus, Grafana, logging solutions).
• Familiarity with security, reliability, and performance best practices for production ML systems.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Electrical Engineering, or a related technical discipline.
• Ability to collaborate effectively with cross-functional teams, communicate technical concepts clearly, and work on-site in a lab and production environment.
• Prior experience in cyber-physical systems, IoT, or sensor networks is an advantage.