Miroslav Román Rosón
Ai Engineering Manager @Frontiers
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WORK HISTORY
Ai Engineering Manager @Frontiers
Lead and mentor a diverse team of data scientists, data engineers, and machine learning engineers.Oversee the development and productization of end-to-end (generative) AI products.Drive technical decisions on machine learning methods, technologies, and engineering best practices.Collaborate with cross-functional teams to design scalable, state-of-the-art infrastructure for serving ML models and LLMs in production.Pioneer research and adoption of best practices in MLOps and LLMOps to build scalable ML pipelines.
EDUCATION
University of Tübingen
Dr. rer. nat. (PhD), International Max Planck Research School
University of Tübingen
Master of Science (M.Sc.)
Universität Osnabrück
Bachelor of Science (B.Sc.)
SKILLS
ABOUT MIROSLAV ROMÁN ROSÓN
Passionate Machine Learning Team Lead with a proven track record in driving AI innovation and leading cross-functional teams to deliver impactful solutions. With extensive experience in developing and deploying cutting-edge AI products across automotive, healthcare, rail, and industrial sectors, I specialize in transforming complex machine learning concepts into scalable, production-ready systems. My journey began at ITK Engineering as an AI Engineer, where I honed my skills in deep learning and computer vision for self-driving cars, time series modeling, and embedded AI. Progressing to an Expert Engineer for Applied Machine Learning, I led multiple teams, provided technical expertise, and managed end-to-end project development and delivery. My role extended to risk project management, ensuring optimal balance between time, budget, and quality. Currently, at Frontiers, I lead a dynamic team of data scientists, data engineers, and machine learning engineers. We focus on developing and productizing end-to-end (generative) AI solutions. I oversee technical decisions on machine learning methodologies, technologies, and engineering best practices. Collaborating closely with product managers and software engineers, I design scalable infrastructures for serving machine learning models and Large Language Models (LLMs) in production. My commitment to advancing MLOps and LLMOps practices drives the creation of efficient, scalable machine learning pipelines.
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