About Me

I am an experienced machine learning engineer with over 4 years of expertise, mainly focusing on time-series forecasting, computer vision (segmentation, object detection), model quantization, and tinyML. My background ranges from developing models to designing ML systems for production-ready deployments. I am particularly interested in making models deployable in different use-case scenarios and designing MLOps architecture, depending on use-case scenarios, including streaming inferencing.

I hold a Master’s degree in Machine Learning from the Indian Institute of Information Technology and Management - Kerala. My experience in different business domains has helped me develop a keen interest in defining success metrics for any ML system with a business use case.

Currently, I am working at Nunam, a Bangalore-based Li-ion battery analytics company. Here, my primary focus is to develop time-series forecasting models that can estimate the health of Li-ion batteries in EVs. At the same time, I also focus on designing the MLOps architecture for model deployment and monitoring.

My primary area of focus revolves around Computer Vision, time-series forecasting, and tinyML, including MLOps frameworks and design patterns. Additionally, I speak at multiple conferences on topics related to the same. A detailed list of my past talks and published papers can be viewed at /publications.