Xindian Long

As a Principal Machine Learning Developer at SAS since 2019, my work centers on translating cutting-edge machine learning research into scalable solutions, particularly in computer vision and large language models. I lead and mentor a deep learning team, driving the design and delivery of systems that address complex, real-world challenges using technologies such as PyTorch, distributed training frameworks like Ray, and GPU-accelerated pipelines on NVIDIA platforms. With over 15 years of experience, I’ve worked across machine learning, computer vision, and image processing, applying advanced algorithms and statistical techniques to deliver practical, high-impact results. My experience includes building end-to-end ML systems, from data pipelines and feature engineering to model training, evaluation, and deployment, leveraging modern MLOps practices and scalable infrastructure such as Kubernetes. I’m especially passionate about bridging research and production, ensuring that the technologies we build are not only innovative, but also robust, scalable, and impactful in real-world applications. I enjoy collaborating across teams and disciplines, and I’m always interested in connecting with others working at the intersection of AI, systems, and applied machine learning.