Sheng Z.

About Sheng Z.

At Amazon AGI, I lead the research and development of cutting-edge large language and multimodal models that power the next generation of AI capabilities. I’m driven by a vision to reduce the cost of intelligence across the stack, making AI more accessible and beneficial to more people. My work focuses on the thoughtful co-evolution of algorithms and systems—the critical intersection that will advance us toward more capable, efficient, and responsible AI.Building from scratch energizes me. I built the M* team from zero, focusing initially on distributed training and shared representations. Since 2018, this team of tech leaders and hackers developed foundation models that now serve millions through AWS services including Amazon Nova, Amazon Q (CodeWhisperer), Titan, Lex, Comprehend, and Kendra. We contributed to the core technology for scalable and fault resilient infrastructure such as Amazon Bedrock and SageMake HyperPod.Throughout this journey, I’ve maintained a core belief: AI should amplify human agency and ingenuity, not replace it. This principle guides my approach to both research and leadership. My leadership philosophy centers on coaching and enabling team members to grow into leaders themselves, creating a multiplier effect that has accelerated our innovation.I\'m an advocate for open source and open collaboration. I have been playing active roles in the open source ecosystem as VP/PMC Chair of Apache MXNet (where I co-authored the Gluon interface), founder of GluonNLP (first to reproduce BERT with record-setting training speeds), member of the Linux AI Foundation’s ONNX Steering Committee, and founding member of the Python Data API Standards Consortium. These roles reflect my belief that accessible tools and standards are essential for an AI future that benefits humanity broadly.I’m now looking to apply this unique combination of foundation model expertise, team building experience, and human-centered vision to lead technical strategy at organizations pushing the boundaries of AGI development—creating intelligence that empowers rather than replaces human potential.All views expressed here are mine and do not represent Amazon.

Experience

1. Senior Applied Science Manager

   Amazon

   Jan 2024 — Present · Manhattan, NY, US

   Foundation model acceleration at Amazon AGI.

Education

• Shanghai Jiao Tong University

  Bachelor of Science - BS, Computer Science

• The University of New Mexico

  Non-degree, Computer Science

• University of Maryland

  Master's degree, Computer Science

Skills

• Software Development
• Python
• Latex
• Unix
• Artificial Intelligence
• Amazon Web Services (Aws)
• High Performance Computing
• Data Mining
• R
• Survival Analysis
• Information Retrieval
• Computational Linguistics
• Dbms
• Computer Science
• Artificial Neural Networks
• Haskell
• Javascript
• C++
• Java
• Ruby
• Hadoop
• Parallel Computing
• Machine Learning
• Scalability
• Hbase
• Html
• C
• Programming
• Algorithms
• Eeg
• Computer Vision
• Matlab
• Microsoft Office
• Natural Language Processing
• Sql
• Linux