Jesse Freitas
Senior ML Engineer at Ironclad
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolJesse Freitas is a Senior ML Engineer with 12 years of software engineering experience, currently focused on building production ML systems at Ironclad after leading generative AI and multilingual NLP efforts at Textio. Previously at Microsoft he shipped large-scale ML features for Word and Editor—bridging LLM research, safety, on-device inference, and Azure ML pipelines—to improve authoring experiences and Copilot integrations. He combines strong backend engineering and test automation skills (notably contributing grading and diffing tooling to the Submitty open-source project) with a practical eye for reliability and security. Jesse holds an MS in Data Science from the University of Washington and a BS in Computer Science from RPI, and he mentors engineers to translate research into product value. Colleagues rely on him for pragmatic end-to-end ML delivery that balances innovation with auditable, production-grade systems.
12 years of coding experience
12 years of employment as a software developer
Master of Science - MS Data Science, Master of Science - MS Data Science at University of WashingtonBachelor of Science (BS) Computer Science, Bachelor of Science (BS) Computer Science at Rensselaer Polytechnic Institute
Stackoverflow
119reputation
5kreached
9answers
0questions
Github Skills (17)
c-language10
testing10
autograd10
cprogramming-language10
data-structures8
data-structure8
algorithms8
unit-testing8
algorithm8
outlook6
msoffice6
angularjs6
office-addin6
office-js6
office3656
Programming languages (3)
Github contributions (5)
Submitty/Submitty
Jan 2014 - Sep 2014
Homework Submission, Automated Grading, and TA grading system.
Role in this project:
Back-end Developer & QA Engineer / Test Automation Engineer
Back-end Developer & QA Engineer / Test Automation EngineerContributions:103 commits, 3 PRs, 8 issues in 7 months
Contributions summary:Jesse added a base class for a Grading Rubric and updated the contributors. They implemented test cases and check classes for a validation suite, demonstrating a focus on automated grading and testing. The user also integrated a diffing library (likely for comparing student submissions to expected outputs) and implemented a function for comparing the output. This indicates a focus on developing backend functionality for an automated grading system.
reactsubmittygrading-systemhomework-serverteaching-tools
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