About

Chiao-Lun Cheng is a highly experienced Full-Stack Machine Learning Engineer who specializes in Deep Learning, Pytorch, Tensorflow, and Keras. With over 14 years of relevant experience, he is well-versed in Transformers, GCNs, LSTMs, biLSTM-CRFs, Computer Vision, Document parsing, and NER. He is also proficient in CUDA streams, Kubernetes, Istio, and NATS.IO message bus, with minor contributions to official TypeScript and Python clients. Cheng has worked extensively with AWS, including Terraform, IAM, VPC management, EKS CNI, and parquet/Athena. He has also worked as a Data Scientist, with skills in Multilevel Modeling, Causal Inference, analysis of AB testing, d-separation, Factorization Machines, Item Response Theory, MCMC with stan/pymc3, Algorithmic Trading research, and Covariance Matrix modeling/Factor Analysis. In addition to his technical skills, Cheng has experience with Numba/Cython, Pyspark, Python Asyncio (expert), MongoDB, Postgres, Lucene, LevelDB, Datadog, Segment, Mode, SQL query optimization, and Parser combinators. He has also worked with Clojure. Currently, Cheng is working as a Machine Learning Engineer at Scale AI, where he is responsible for model training and deployment systems based on Kubernetes/NATS.IO service bus, autoscaling to and from zero with no session losses. He has previously worked at Scale AI as a Machine Learning Engineer, where he conceived and implemented low-lag ETL from MongoDB to Athena from scratch. He has also worked as a self-employed Data Scientist, where he built predictive models for a European supermarket chain to optimize workforce scheduling and utilized state-of-the-art neural networks for production line defect detection in electronic components. Cheng holds a PhD in Physical Chemistry and Computational Physics from the Massachusetts Institute of Technology, where he also completed his undergraduate studies in Chemistry, Physics, and Biochemistry. He completed his Bachelor's degree in Chemistry and Biology from the University of California, Irvine, and his high school education from Dunman High. Cheng's Tech Stack includes ML, AI, Research Scientist, Amazon Athena, Kubernetes, SQL, AWS, Python, MongoDB, Keras, Computer Vision, Terraform, Data Scientist, Deep Learning, test, Typescript, Tensorflow, Postgres, Pytorch, Clojure, Snowflake, E