Design, build, and deploy production-grade ML models for predictive analytics and condition monitoring applications across tire products and manufacturing domains, moving solutions from prototype to operational systems used by engineering teams
Apply physics-informed and hybrid physics-ML approaches that embed domain engineering knowledge directly into model architectures, ensuring predictions are physically consistent and trusted by engineering stakeholders
Develop and deploy computer vision systems for image-based inspection and classification tasks
Build and maintain scalable data pipelines for ingesting, processing, and serving high-frequency sensor streams from connected physical systems, supporting both real-time and batch analytics use cases
Implement Generative AI and LLM-based tools to enhance engineering productivity, including knowledge retrieval systems and AI-assisted workflows, with emphasis on on-premises ...