Principal Machine Learning Engineer at Capital One
Chicago, Illinois, United States
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Summary
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Abbas Shakiba is a Principal Machine Learning Engineer based in Chicago with over a decade of experience building production ML and data systems across finance and insurance. He combines hands-on model development and MLOps with a strong software engineering background—earlier roles ranged from senior data engineering to full-stack contributions on open-source JavaScript tooling. Abbas has a track record of improving reliability and developer experience, shown both in enterprise ML projects at Capital One and in OSS work that refined Rollbar.js error handling and SVG/physics tooling. He holds graduate training in computer science and multiple specialized nanodegrees in ML and full-stack development, reflecting a commitment to continuous learning and pragmatic engineering. A practical problem-solver, he often bridges gaps between research, deployment, and front-end usability to ship measurable business impact.
13 years of coding experience
10 years of employment as a software developer
Diploma Mathematics and Physics, Diploma Mathematics and Physics at Shahid Ebrahimi High school
Nanodegree Machine Learning with Pytorch, Nanodegree Machine Learning with Pytorch at Udacity
Computer Science, Computer Science at University of Chicago
Bachelor of Science (BS) Computer Software Engineering, Bachelor of Science (BS) Computer Software Engineering at Shiraz University
Master of Science (M.Sc.) Computer Science, Master of Science (M.Sc.) Computer Science at Bowling Green State University
SVG to PNG/JPEG command-line tool and Node.js module
Role in this project:
Full-stack Developer
Contributions:1 review, 62 commits, 7 PRs in 7 years 5 months
Contributions summary:Abbas primarily focused on refining the command-line interface and node module aspects of the project. They improved parameter parsing for image export quality, dimensions, and file formats. The user also refactored the codebase, improved documentation, and introduced features such as setting the viewbox from the SVG file.
Error tracking and logging from Javascript to Rollbar
Role in this project:
Full-stack Developer
Contributions:4 releases, 17 commits, 14 PRs in 1 month
Contributions summary:Abbas primarily focused on enhancing the functionality and maintainability of the Rollbar.js library. Their contributions included refactoring and improving error transformation logic by passing items to transforms, and also modifying the build and release process by updating the library version. The user also made critical improvements to the codebase, which ensures it integrates smoothly with the browser environment.
reactexpressjsloggererror-monitoringjavascript
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Abbas Shakiba - Principal Machine Learning Engineer at Capital One