Summary
Runsheng Song is a Senior Software Engineer with 11 years of experience building production web applications and machine learning systems, currently focused on sustainability tooling at AWS. He combines deep Python and ML expertise with hands-on backend engineering—designing RESTful APIs, asynchronous task pipelines, and Dockerized deployments for scalable services. His background spans applied ML for compliance and document review at Lyft, carbon footprint and life cycle assessment software at Amazon, and an academic PhD-driven project (CLiCC) that predicted chemical lifecycle impacts via neural networks. Comfortable across the stack, he has shipped systems using TensorFlow/Keras, Flask/Django, Celery, RabbitMQ, and cloud orchestration on AWS. Seeking roles in Data Science, MLE, or SDE, he brings domain fluency in environmental science plus a track record of turning research prototypes into user-facing, production-ready platforms. A less obvious strength is his ability to bridge rigorous academic research with pragmatic engineering to deliver tools that serve both scientists and large-scale product teams.
11 years of coding experience
10 years of employment as a software developer
Bachelor of Engineering (BEng) Environmental Engineering Technology/Environmental Technology, Bachelor of Engineering (BEng) Environmental Engineering Technology/Environmental Technology at Huazhong University of Science and Technology
Doctor of Philosophy - PhD Environmental Science, Doctor of Philosophy - PhD Environmental Science at Bren School of Environmental Science & Management - University of California, Santa Barbara
Chinese, English