Fractional CTO Focused On Search, Machine Learning And Natural Language Processing
Charlotte Metro United States
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Summary
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Senior
🎓
Top School
Grant Ingersoll is a seasoned technology leader and fractional CTO with over 20 years of experience specializing in search, machine learning, and natural language processing. He co-founded Lucidworks, led large engineering organizations including Wikimedia’s tech team, and authored the practical guide Taming Text, reflecting deep expertise in information retrieval and NLP. Grant blends hands-on engineering—contributing to Apache Lucene/Solr and Mahout and teaching public courses on search and ML—with strategic leadership, helping organizations stabilize platforms, hire and scale teams, and define technical roadmaps. As founder of Develomentor, he offers plug-and-play C-level leadership that bridges gaps during transitions and accelerates product launches for enterprises and startups alike. His open-source work and course repositories show a pattern of improving search relevance, indexing pipelines, and developer tooling—skills he pairs with strong communication as a public speaker and podcast host. Based in Charlotte, he is equally comfortable tuning fuzzy-matching algorithms in code or guiding executive teams through complex replatforms.
19 years of coding experience
20 years of employment as a software developer
BA Math Computer Science, BA Math Computer Science at Amherst College
MS Computer Science, MS Computer Science at Syracuse University
Public repository for the Search Fundamentals course taught by Daniel Tunkelang and Grant Ingersoll. Available at https://corise.com/course/search-fundamentals?utm_source=daniel
Role in this project:
Full-stack Developer
Contributions:2 releases, 32 commits, 8 PRs in 9 months
Contributions summary:Grant primarily worked on developing and refining the application's codebase, making updates and fixes across multiple files. They updated Gitpod commands to improve the development environment and made various UI fixes to improve the autocomplete feature. The user also made changes to indexing and search functionality.
Public repository for the Search with Machine Learning course taught by Daniel Tunkelang and Grant Ingersoll. Available at https://corise.com/course/search-with-machine-learning?utm_source=daniel.
Role in this project:
Full-stack Developer
Contributions:1 review, 144 commits, 127 PRs in 10 months
Contributions summary:Grant appears to be a full-stack developer, primarily focusing on setting up and building out the core functionality for a search application utilizing machine learning principles. Their commits indicate the implementation of Logstash configurations for indexing data, including product and query data, and the creation of a Flask-based web application. The user also established a basic structure for the frontend and backend by making changes to template and python files.
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Grant Ingersoll - Fractional CTO Focused On Search, Machine Learning And Natural Language Processing