I have over 10 years of experience developing AI systems across diverse industries. I’ve architected and deployed solutions in natural language processing, speech recognition, predictive modeling for automotive pricing, and industrial condition monitoring systems that deliver measurable business value.
I believe successful AI implementation requires both deep theoretical understanding and practical engineering expertise. This philosophy has guided my career path, where I’ve intentionally balanced research and development roles with hands-on engineering positions to master both the science and craft of machine learning. This dual perspective enables me to translate complex algorithms into robust, scalable solutions.
My experience spans from researching cutting-edge algorithms in R&D environments to building production-ready systems that solve real-world business problems. I excel at bridging the gap between theoretical possibilities and practical implementations, ensuring AI solutions are not just innovative but also reliable, maintainable, and aligned with business objectives.