Chester Curme
Machine Learning Engineer at LangChain
Boston, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolChester Curme is a Machine Learning Engineer with nine years of experience building production-grade AI systems, currently contributing to LangChain after leadership roles at Microsoft, Evisort, and Kensho. He holds a Ph.D. in Physics from Boston University and blends deep quantitative rigor with practical ML engineering, having led teams that translate research into deployable products. At LangChain he works on developer-facing tooling and has contributed to the langgraph project to improve human-in-the-loop conversational examples, highlighting a focus on usable agent workflows. Chester’s background spans finance-grade quantitative modeling to applied AI at scale, and he brings an unusual combination of academic depth and hands-on full-stack implementation to developer tools in the LLM ecosystem.
9 years of coding experience
12 years of employment as a software developer
BA Physics and Mathematics, BA Physics and Mathematics at Middlebury CollegeWeston High SchoolDoctor of Philosophy (Ph.D.) Physics, Doctor of Philosophy (Ph.D.) Physics at Boston University
Github Skills (7)
jupyter-notebook10
python10
langchain10
integrations9
integrate9
tooling9
conversational-ai8
Programming languages (8)
Github contributions (5)
langchain-ai/langgraph
Jan 2024 - Mar 2025
Build resilient language agents as graphs.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:29 reviews, 48 PRs, 76 pushes in 1 year 2 months
Contributions summary:Chester primarily contributed to updating and improving the examples, specifically the "human-in-the-loop" notebook within the `langgraph-ai/langgraph` repository. They modified the human-in-the-loop notebook, integrating with search tools and adding code for a conversational human-in-the-loop experience. These updates involved changes to the notebook's code, including code cells and outputs, as well as restructuring the introduction of the conversational human-in-the-loop section. This suggests a focus on enhancing the user experience and functionality of the LangGraph examples.
ccurme/langchain
Jan 2023 - Mar 2024
⚡ Building applications with LLMs through composability ⚡
Contributions:50 pushes, 20 branches in 1 year 2 months
composability
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