Jack Kwok, Deep Learning Developer in San Francisco, CA, United States
Jack Kwok

Deep Learning Developer in San Francisco, CA, United States

Member since March 29, 2019
Jack has over a dozen years of experience developing complex software systems. He is experienced in applying deep learning techniques to solve computer vision problems such as object detection, multi-object tracking, and ND semantic segmentation, to name a few. Jack currently works in applying state-of-the-art deep learning computer vision models, and algorithms to solve autonomous driving problems. He has an expert rating at Kaggle.
Jack is now available for hire

Portfolio

Experience

  • Python 3, 6 years
  • Deep Learning, 3 years
  • Computer Vision, 3 years
  • PyTorch, 2 years

Location

San Francisco, CA, United States

Availability

Part-time

Preferred Environment

Python, Pytorch, Linux, Windows, AWS

The most amazing...

...project I have worked on involved building a neural network from scratch to recognize handwritten digits. It led me to pursue a career in deep learning.

Employment

  • Software Engineer: Computer Vision, and Machine Learning

    2017 - PRESENT
    Lyft Autonomous Driving Center
    • Applied deep learning, and computer vision algorithms to solve autonomous driving problems.
    Technologies: PyTorch, TensorFlow, Python, OpenCV, AWS, Deep Learning, Object Detection, Object Tracking.
  • Artificial Intelligence Fellow

    2017 - 2017
    Insight Data Science
    • Developed a computer vision system based on a convolutional neural network that automatically annotates post-hurricane flooded roads on satellite imagery.
    • Developed an open-source project on GitHub.
    • Researched, and published a blog post about the use of deep learning for disaster recovery.
    Technologies: Deep Learning, Semantic Segmentation, Keras
  • Staff Software Engineer

    2015 - 2017
    LinkedIn
    • Helped build LinkedIn's video platform from scratch.
    • Wrote a technical blog post on building a Native video player library for Android.
    Technologies: Java, Video Codecs, Mobile Devices
  • Software Architect

    2011 - 2015
    Trulia
    • Scaled our mobile platform to over a dozen apps across iOS, and Android. This grew the audience over ten times. Trulia mobile apps are top-rated by users, and frequently selected for prestigious editorial features by Apple, Google Android (Editors' Choice, and Staff Pick), Amazon, and Samsung.
    • Developed and built projects for iOS and Android involving geofencing and geospatial data, user data synchronization, cross-platform communication, and natural language processing.
    Technologies: Android, iOS, REST API
  • Technical Leader

    2006 - 2011
    Cisco
    • Led the architectural designs of Cisco Jabber (an enterprise VoIP app) on Android. Worked with product managers to translate business needs into technical specifications. Worked with cross-functional teams to define requirements, interfaces, and implementation approaches, and led a group of six talented Android developers to build out layered components of the application from scratch.
    • Extended the Blackberry client with innovative voice features, coordinated development activities, and mentored junior engineers.
    Technologies: Android, VoIP, Codecs
  • Senior Software Engineer

    2004 - 2006
    Weathernews Americas
    • Developed the prototype, architecture, design, and implementation of Weathernews LiveLocal. LiveLocal is the US’s first streaming video application bringing videos from local broadcast TV stations to cell phones.
    Technologies: Mobile Video

Experience

  • Deep Learning for Disaster Recovery (Development)
    https://github.com/jackkwok/neural-road-inspector

    Using state-of-the-art deep learning methods, I attempted to automatically annotate flooded, washed out, or otherwise severely damaged roads. My goal was to create a tool that could help detect, and visualize anomalous roads in a simple user interface.

    For details, see blog post:
    https://blog.insightdatascience.com/deep-learning-for-disaster-recovery-45c8cd174d7a

Skills

  • Languages

    Python 3, Java
  • Libraries/APIs

    PyTorch, Keras, Scikit-learn, NumPy, OpenCV, Pandas, SciPy, TensorFlow
  • Tools

    Scikit-image, AWS CLI
  • Other

    Deep Learning, Computer Vision, Object Detection, Object Tracking, Image Processing, Linear Algebra, Demand Sizing & Segmentation, Convolutional Neural Networks, Semantics, Video Codecs, Recurrent Neural Networks
  • Platforms

    Kubernetes

Education

  • Master of Engineering degree in Computer Science
    2001 - 2002
    Massachusetts Institute of Technology - Cambridge, MA
  • Bachelor of Science degree in Computer Science
    1997 - 2001
    Massachusetts Institute of Technology - Cambridge, MA
  • Bachelor of Science degree in Mathematics
    1997 - 2001
    Massachusetts Institute of Technology - Cambridge, MA

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