Summary
Jian Shen is a founding deep learning engineer with eight years of experience building production-grade ML systems at the intersection of LLMs, multimodal models, and generative AI for real-world applications. He led R&D efforts from 3D computer vision for LiDAR at Velodyne to transformer- and diffusion-based models for drug generation, including training a Llama3-based drug-generation model and guiding models that influenced actual drug production. As founder/tech lead at SAGI he architected multi-agent LLM + RAG systems delivering PhD-level QA performance with a 32B model and built multimodal treatment-suggestion pipelines using DPO. His background in inorganic chemistry and hands-on research roles gives him a rare blend of domain science intuition and deep engineering rigor. Based in Albany, NY, Jian is self-taught in ML, resiliently transitioning from chemistry to leading applied AI projects that span academia, startups, and industry. He’s particularly adept at turning advanced research ideas into deployable systems that impact decision-making in high-stakes domains.
8 years of coding experience