Grant Ingersoll
Fractional CTO Focused On Search, Machine Learning And Natural Language Processing
Charlotte Metro United States
Summary
👤
Senior🎓
Top SchoolGrant 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.
20 years of coding experience
20 years of employment as a software developer
BA Math, BA Math at Amherst CollegeMS Computer Science, MS Computer Science at Syracuse UniversityBuffalo High School
Spanish
Stackoverflow
1reputation
0reached
1answer
0questions
Github Skills (28)
lucene10
opensearch10
matrix10
python10
clustering-algorithm10
machine-learning10
solr10
flask-ask10
java10
searching10
vector10
javas10
mat10
logstash10
text-processing10
Programming languages (11)
Github contributions (5)
gsingers/search_with_machine_learning_course
Dec 2021 - Oct 2022
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
Full-stack DeveloperContributions: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.
machine-learning
tamingtext/book
Dec 2011 - Feb 2015
Taming Text Book Source Code
Role in this project:Back-end Developer
Back-end DeveloperContributions:39 commits, 1 PR, 1 push in 3 years 2 months
Contributions summary:Grant primarily contributed to the project by fixing typos, modifying and improving existing code. The user made changes to Java source files, specifically related to fuzzy matching algorithms, text classification, and question answering. They also updated dependencies, configuration files and incorporated tech editor comments. These changes suggest a focus on refining the core functionality of the text processing and information retrieval capabilities of the book's examples.
python
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