Michael Chambers, Developer in Atlanta, GA, United States
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Michael Chambers

Verified Expert  in Engineering

Software Developer

Atlanta, GA, United States
Toptal Member Since
October 31, 2019

Michael is a full-stack web engineer with a track record in delivering performant applications as well as a background in data-centric UI design. With eight years of experience in software development, Michael's focus lies in front- and back-end web technologies like React, Vue.js, and Node.js. While getting his Ph.D., Michael developed automated systems for the management, processing, and interactive visualization of large scientific datasets.


Amazon Web Services (AWS), Firebase, GraphQL, DigitalOcean, Netlify, Heroku...
University of California, Los Angeles
R, Java, Python, Node.js, JavaScript




Preferred Environment

MongoDB, Node.js, Express.js, Vue, React

The most amazing...

...thing I've ever worked on was a full rework of the GraphQL data layer for a mentor social network/web app with a large established user base.

Work Experience

Full-stack Developer

2019 - PRESENT
  • Worked with a non-profit to modernize their online presence, incorporating custom branding, best-practices CSS, CMS functionality, and a responsive mobile-first design.
  • Deployed applications to cloud-based service providers, including AWS, Heroku, Netlify, and DigitalOcean.
  • Delivered a single-page app for event booking using React/Redux, GraphQL, and a Firebase data back end.
  • Reworked a GraphQL data layer for a mentor/social media application with an active user base and complex data requirements, making it more performant and stable.
Technologies: Amazon Web Services (AWS), Firebase, GraphQL, DigitalOcean, Netlify, Heroku, MongoDB, Node.js, Vue, React, CSS, HTML, JavaScript

Software Researcher/Lecturer

2007 - 2018
University of California, Los Angeles
  • Developed Java and Python libraries to automate the analysis of unstructured research data, including data extraction, transformation/processing, modeling, and visualization.
  • Developed an open-source R library to address common analytical procedures dealing with high-throughput genomic sequencing data.
  • Implemented a software suite to integrate real-time time-series gene expression profiles with clinical and patient outcome data.
  • Utilized generalized linear models, Hidden Markov models, and network analysis to identify the gene clusters responsible for a class of fatal neurological disorders.
  • Applied the principles of machine learning, including SVNs, k-means and k-modes clustering, and ensemble learning to solve real-world problems.
  • Presented my findings and techniques at conferences and published results in peer-reviewed academic journals.
Technologies: R, Java, Python, Node.js, JavaScript

Defined a Regulatory Genetic Network Using Statistical Modeling and Machine Learning

Worked on the exploration and definition of a regulatory genetic network involved with the early specification of nervous tissue, as well as a class of fatal developmental disorders. Constructed an automated ETL/analysis pipeline using Python, Java, and R to process large quantities of unstructured research and clinical data. Results were published in BMC Genomics, 2016
2007 - 2014

Ph.D. in Bioinformatics

University of California, Los Angeles - Los Angeles, CA

2006 - 2007

Master of Science Degree in Chemistry

Georgia Institute of Technology - Atlanta, GA

2003 - 2006

Bachelor of Science Degree in Chemistry

Georgia Institute of Technology - Atlanta, GA


React, Node.js, D3.js, Vue, Vue 2, Scikit-learn, TensorFlow




Python, R, HTML, CSS, GraphQL, JavaScript, Java


MongoDB, MySQL




Heroku, Netlify, DigitalOcean, Firebase, Amazon Web Services (AWS)

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