# Evan Sangaline

> Principal AI Engineer at Sindri

Location: Brooklyn, New York, United States
Profile: https://flows.cv/evansangaline

I'm a full stack software engineer with a strong background in statistics and data science. My background was originally in nuclear physics where I wrote high performance C++ code to analyze petabytes of data and helped expand the infrastructure necessary for such analyses. After leaving academia, I founded Intoli where I've had the opportunity to build a variety of web services in-house as well as to work with dozens of other companies through contracting and consulting arrangements. I currently work at TenantBase where I lead our data science efforts and do full stack web development.

## Work Experience
### Principal AI Engineer @ Sindri
Jan 2023 – Present | Brooklyn, New York, United States

### Chief AI Officer @ TenantBase
Jan 2022 – Present | Santa Monica, California, United States

### Vice President of Artificial Intelligence @ TenantBase
Jan 2020 – Jan 2022 | Santa Monica, California, United States

### Lead Machine Learning Engineer @ TenantBase
Jan 2019 – Jan 2020 | Santa Monica, California, United States

### Full Stack Software Engineer @ TenantBase
Jan 2017 – Jan 2019

### Cofounder & Full Stack Software Engineer @ Intoli
Jan 2015 – Present | Gainesville, FL

### Scientific Software Engineer @ National Superconducting Cyclotron Laboratory
Jan 2014 – Jan 2015 | East Lansing, MI
Developed a C++ Markov Chain Monte Carlo (MCMC) simulation framework with support for Gaussian process likelihood approximations. Worked with scientists across multiple disciplines to integrate cutting edge statistical techniques into their analyses. Made the first determination of the nuclear equation of state from experimental data, a longstanding goal in the field of nuclear physics.

### Graduate Student Researcher @ Lawrence Berkeley National Laboratory
Jan 2011 – Jan 2014
Developed high‑performance C++ code to analyze petabytes of experimental data on a distributed infrastructure. Designed the first algorithm for machine-learning driven particle identification in high energy physics. Awarded the prestigious RHIC & AGS Thesis Award for most outstanding nuclear or high energy physics thesis.


## Education
### PhD in Physics
University of California, Davis

### MS in Physics
University of California, Davis

### BA in Physics
Bard College


## Contact & Social
- LinkedIn: https://linkedin.com/in/sangaline

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Source: https://flows.cv/evansangaline
JSON Resume: https://flows.cv/evansangaline/resume.json
Last updated: 2026-03-31