Jordan Burgess, Software Developer in Cambridge, United Kingdom
Jordan Burgess

Software Developer in Cambridge, United Kingdom

Member since July 1, 2017
Jordan is a machine learning researcher and full-stack engineer. He works as a research scientist at Amazon on in NLP and ML. He has six years professional software development experience working in data science, front-end web, and Android technologies. Jordan has a master's degree in machine learning from Cambridge University and a M.Eng. degree in engineering from Cambridge and MIT.
Jordan is now available for hire

Portfolio

  • Amazon
    Amazon Web Services (AWS), TensorFlow, Natural Language Processing (NLP), AWS...
  • Bloomsbury AI
    React, Flask, Pandas, NumPy, Scikit-learn, Python
  • Lumi
    Java, Android, JavaScript, Python

Experience

Location

Cambridge, United Kingdom

Availability

Part-time

Preferred Environment

PyCharm, Git, Unix

The most amazing...

...machine learning idea I've developed is a way to create one-shot learning classifiers using a Bayesian update on existing CNNs.

Employment

  • Applied Scientist

    2017 - 2019
    Amazon
    • Researched and developed spoken language understanding (SLU) models for Amazon Alexa.
    • Built custom machine translation pipeline to use existing English data, halving the time and data requirements to bootstrap Alexa’s natural language understanding (NLU) models for new languages (saving $ millions).
    • Refactored a large, legacy codebase to unify every locale's process for training NLU models using test-driven development. Sped up the ordering process 25x. Reduced requirements for managing the process from 20 to 6 FTEs.
    • Mentored the team on rigorous software engineering practices. Became one of six "trusted reviewers" after only five months.
    Technologies: Amazon Web Services (AWS), TensorFlow, Natural Language Processing (NLP), AWS, Python
  • Senior Machine Learning Engineer

    2016 - 2017
    Bloomsbury AI
    • Developed machine learning models for question answering, combining research in deep learning and machine reasoning using Python, Sklearn, and TensorFlow.
    • Built a question-answering interaction and debugging tool in React.
    • Built an interactive question-answering bot using probabilisitic logic.
    Technologies: React, Flask, Pandas, NumPy, Scikit-learn, Python
  • Software Engineer

    2014 - 2015
    Lumi
    • Led development of a web app (Python/JavaScript) and instigated a user-centered redesign which increased retention 400%.
    • Switched to full-time Android development, helping create an app used by over 100k people.
    Technologies: Java, Android, JavaScript, Python
  • Co-founder and CTO

    2013 - 2014
    Elective.com
    • Built a platform to connect patients with worldwide medical providers.
    • Built partnerships with international dentists and booked over £160,000 worth of consultations.
    Technologies: PostGIS, Django, Python
  • Technology Scholar

    2008 - 2012
    Cambridge Consultants
    • Debugged processor design using an FPGA (C/Python/Assembly).
    • Led the technical team in creating a touchscreen device to show appliance-level real-time energy use.
    Technologies: Assembly Language, C, Python

Experience

  • One-Shot Learning in Discriminative Neural Networks
    https://arxiv.org/abs/1707.05562

    We consider the task of one-shot learning of visual categories. In this paper we explore a Bayesian procedure for updating a pretrained convnet to classify a novel image category for which data is limited. We decompose this convnet into a fixed feature extractor and softmax classifier. We assume that the target weights for the new task come from the same distribution as the pretrained softmax weights, which we model as a multivariate Gaussian. By using this as a prior for the new weights, we demonstrate competitive performance with state-of-the-art methods whilst also being consistent with 'normal' methods for training deep networks on large data.

Skills

  • Languages

    Python, JavaScript, C, Assembly Language, Java
  • Other

    Machine Learning, Natural Language Processing (NLP), AWS, Lean Startups, Unix Shell Scripting, Lean Development, Deep Learning
  • Frameworks

    Django, Flask, Svelte
  • Tools

    Git, MATLAB, PyCharm, Sketch
  • Paradigms

    Agile, Agile Software Development
  • Libraries/APIs

    Scikit-learn, NumPy, Pandas, TensorFlow, React, PyTorch
  • Platforms

    Unix, Amazon Web Services (AWS), iOS, Android, Meteor
  • Storage

    PostGIS, PostgreSQL, MongoDB

Education

  • Master's degree (M.Phil.) in Machine Learning, Speech and Language Technology
    2015 - 2016
    University of Cambridge - Cambridge, UK
  • Master of Engineering degree (M.Eng.) in Manufacturing Engineering
    2009 - 2013
    University of Cambridge - Cambridge, UK
  • Visiting Scholar in Engineering and Computer Science
    2011 - 2012
    MIT - Cambridge, MA

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