Kuan Zhou

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I am a machine learning engineer with a scientific research background in physics.



Exploring the synergy between science and technology, particularly the exciting field of artificial intelligence.


  • Programming language: Python, C++, Java, Golang, JavaScript
  • AI framework: Pytorch, JAX, TensorFlow
  • Distributed system: Torch distributed, DeepSpeed
  • ML compiler: MLIR, TVM, LLVM
  • MLOps: Docker, gRPC, Kubernetes, Kubeflow, MLFlow, Weights & Biases
  • Science: Mathematica, Julia, Matlab
  • Others: TeX, SQL, Spark, Hadoop, ORTools, Numba, CUDA


  • Principal Engineer at SambaNova Systems, April 2020 - Present
    • Tech lead in containerizing and deploying generative AI models onto Kubernetes platform SambaStudio
      • Led a 5+ engineers team to deploy 10+ foundation model based solutions to business customers
      • Prototyped the generative AI model deployment pipeline in collaboration with Kubernetes platform team
      • Built general and extensive infrastructure for continuous model integration and deployment
      • Standardized the model bringup and integration procedure via refactoring ML applications
    • Co-designed and co-developed distributed learning infrastructure for extreme large models
      • Overlapping gradient synchronization in machine learning(U.S. patent pending with filing date 2/14/2022)
      • System of heterogeneous reconfigurable processors for the data parallel execution of applications(U.S. patent pending with filing date 9/9/2022)
    • Contributed in core features of SambaNova AI framework
      • Designed, implemented and maintained a binary data extractor as bridge between compiler and runtime
      • Refactored and upgraded AI framework codebase to support functional programming style dataflow execution
      • Implemented various deep learning operators from compiler low level kernels to AI framework end to end
      • Optimized performance of deep learning models(HIPNN etc.) based on SambaNova AI framework and dataflow architecture
      • Integrated TensorBoard as visualization and accuracy debugger tool into SambaNova AI framework
  • Software Engineer - Machine Learning at Petuum, February 2019 - March 2020
    • Leveraged OCR engines and deep learning models to process logistic bills automatically with 0.87 accuracy
    • Collaborated in implementation of various anomaly detection models for equipment health prediction
    • Contributed in machine learning pipeline refactoring and model improvement based on various use cases
  • Artificial Intelligence Fellow at Insight Data Science, June 2018 - September 2018
    • Architected SketchTML that takes in several hand drawn sketches and produces an interactive HTML website
    • Leveraged the framework of pix2code to build a more robust image captioning model with different styles
    • Improved BLEU score up to 0.88 through inventive data augmentation methods and weighted loss functions