Summary
Ali Mosavian is a pragmatic, hands-on AI and machine learning engineer and founder with over two decades of programming experience and more than a decade focused on production ML systems. He co-founded startups and served as ex-CTO and technical lead, architecting event-driven, microservice platforms and designing hardware-integrated data pipelines that powered real-time predictions at scale. Ali has repeatedly taken research-grade models into production—building recommendation systems, RAG-based AI assistants, video-based physiological sensing, and hybrid recommender architectures—often optimizing for cost and latency across global deployments. Comfortable across the stack, he combines deep learning, classical signal processing, and system-level engineering with tools like LangChain, FastAPI, CatBoost, TensorFlow/PyTorch, Docker and cloud platforms. Notably, his open-source and build-system work (e.g., Maven migration and build refactors on jmxtrans) shows a focus on reliable infrastructure as much as model accuracy. Based in Sweden, he excels at turning ambitious ideas into fast, pragmatic products through rapid iteration and unconventional problem-solving.
12 years of coding experience
17 years of employment as a software developer
Master of Science - MS, Computer Science & Machine learning, Master of Science - MS, Computer Science & Machine learning at KTH Royal Institute of Technology