Hector Berdugo
Senior Software Engineer at Fellow - AI Meeting Assistant
Ottawa, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolHector Berdugo is a senior software engineer with 11 years of experience building and scaling SaaS platforms, currently leading core engineering at Fellow where he helped architect AI-driven meeting transcription, summarization, and integrations used by thousands of teams. He excels across the full stack—Python, TypeScript, React, MySQL/Postgres—designing scalable APIs, secure RBAC systems, and data pipelines while owning features end-to-end from ideation to product iteration. As a founding engineer he built the Model Context Protocol server powering Fellow’s AI integrations and has deep experience embedding AI into workflow automation. His background includes ML-focused contributions to open-source time-series anomaly detection and research-grade data ingestors for MIT, reflecting a strong bridge between applied machine learning and production engineering. Comfortable in startup environments, he pairs rapid delivery with user-driven iteration and mentorship. Based in Ottawa, he’s also curious about Web3 infrastructure as a way to simplify complex processes beyond traditional SaaS.
11 years of coding experience
7 years of employment as a software developer
Bachelor of Science (B.S.), Computer Engineering, Bachelor of Science (B.S.), Computer Engineering at Universidad Simón BolívarMaster's degree, Computer Science, Master's degree, Computer Science at Carleton UniversityExchange Student - Informatics Engineering, Computer Science, Exchange Student - Informatics Engineering, Computer Science at Universidad de Granada
Spanish, English
Github Skills (9)
machine-learning10
jupyter-notebook10
time-series10
unsupervised-learning10
python10
data-science10
data-analysis10
pandas9
deep-learning8
Programming languages (1)
Github contributions (5)
sintel-dev/Orion
Mar 2019 - Apr 2019
Unsupervised time series anomaly detection library
Role in this project:
Data Scientist
Data ScientistContributions:36 commits in 26 days
Contributions summary:Hector primarily focused on fixing and updating example notebooks within the `orion` library, which is designed for unsupervised time series anomaly detection. Their contributions included resolving issues in notebooks related to data analysis and dummy pipelines, correcting errors, and improving the clarity of messages. They also addressed specific exceptions within the `orion` codebase, likely improving the usability of the library's command-line interface.
benchmarkingdata-sciencedeep-learningunsupervised-learninganomaly-detection
Hector-hedb12/Cardea
Feb 2019 - May 2019
An open source library for using machine learning in healthcare.
Contributions:4 PRs, 22 pushes, 10 branches in 3 months
pythonhealthcaremachine-learning
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