David Mezzetti
Founder CEO at NeuML
Washington DC-Baltimore Area United States
Summary
🤩
Rockstar🎓
Top SchoolDavid Mezzetti is a founder and CEO with 11+ years driving AI, NLP and ML products and companies, currently building NeuML and the open-source txtai embeddings database for semantic search and LLM orchestration. He combines hands-on backend and DevOps expertise—implementing API infrastructure, AWS deployments, reindexing and performance optimizations—with founder-level skills in strategy, operations and M&A from scaling Data Works to a 50+ person acquisition. His work on paperai shows domain focus in scientific and medical literature search, improving memory and query features for production search workflows. Based in the DC-Baltimore area, he pairs practical engineering depth with advisory and speaking roles to help organizations operationalize retrieval-augmented generation and AI-driven literature analysis.
10 years of coding experience
17 years of employment as a software developer
BS Computer Systems Engineering, BS Computer Systems Engineering at Rensselaer Polytechnic Institute
Stackoverflow
51reputation
592reached
3answers
0questions
Github Skills (23)
python10
apidoc10
machine-learning10
searching10
api10
sql10
nlp10
dockers9
report-builder9
docker9
databases9
aws9
report-generator9
database9
scikit-learn7
Programming languages (9)
Github contributions (5)
neuml/paperai
Jul 2020 - Jan 2023
📄 🤖 Semantic search and workflows for medical/scientific papers
Role in this project:
Back-end Developer
Back-end DeveloperContributions:17 releases, 191 commits, 7 PRs in 2 years 6 months
Contributions summary:David primarily contributed to the back-end logic of the paperai project, focusing on features related to search functionality, reporting, and data retrieval. Their work included implementing wildcard query support, cleaning up code, and improving memory performance for the embeddings index. The user also addressed setup issues and added support for custom transformer models for QA extraction. These contributions enhanced the search capabilities and report generation features of the AI-powered literature discovery engine.
ai-poweredscientific-papersmachine-learningreviewdiscovery
neuml/txtai
Aug 2020 - Jan 2023
💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
Role in this project:Backend Developer & DevOps Engineer
Backend Developer & DevOps EngineerContributions:45 releases, 24 reviews, 925 commits in 2 years 5 months
Contributions summary:David's contributions focused on the database/backend and infrastructure aspects of the txtai project. The commits included testing and implementing new features in the models module. Additional commits addressed partial query results during clustering and enhanced the system's ability to reindex embeddings, suggesting a focus on database optimization. Moreover, the user's work involved setting up and configuring the API, specifically for processing JSON data and deploying with AWS, implying proficiency with DevOps and API infrastructure.
ai-poweredpythonapproximate-nearest-neighbor-searchsemantic-similaritysimilarity-search
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