# Glenn LeBlanc

> Software Engineer

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

Software engineer interested in data, distributed systems, and math.

## Work Experience
### Software Engineer @ Airtable
Jan 2026 – Present | New York City Metropolitan Area
Infrastructure engineering

### Engineering @ Applied Intuition
Jan 2024 – Jan 2025 | Mountain View, California, United States
Secret stuff in the physical AI space (🤫)

### Software Development Engineer II @ Amazon Web Services (AWS)
Jan 2024 – Jan 2024 | Palo Alto, California, United States

### Software Development Engineer I @ Amazon Web Services (AWS)
Jan 2022 – Jan 2024 | Palo Alto, California, United States
Developed features for Aurora Limitless Database spanning both data plane and control plane. Designed and implemented modified query planning and execution within the PostgreSQL engine, and CRUD APIs across various micro services inside the AWS Aurora control plane to support Aurora Limitless features including horizontal scaling and snapshot data migration.

### Engineering Intern - Sensor Fusion / Data Science @ Nauto
Jan 2022 – Jan 2022 | Palo Alto, California, United States
Developed logging and data analysis software to interface with NovAtel INS hardware. Implemented and validated TensorFlow vehicle dynamics model as part of effort to port an onboard GNSS & IMU sensor fusion algorithm into an offboard cloud model. Prototyped tuning method for parametrized on-device orientation anomaly detection using PySpark and Databricks, demonstrating 30% increase in test F1 scores and helping to reduce LTE costs.

### Research Intern - Bay Area Neutron Group @ Berkeley Lab
Jan 2020 – Jan 2021 | Berkeley, California, United States
Coauthor of "Modeling ionization quenching in organic scintillators" (Materials Advances June 2022). Contributed to C++ data analysis framework to develop Monte-Carlo fitting routine solving longstanding (3+ years) problem group had faced concerning biased model fitting using least squares. Presented work at 2021 IEEE Nuclear Science Symposium.

### Research Intern - Quantum AI Lab @ NASA Ames Research Center
Jan 2019 – Jan 2019 | Mountain View, California, United States
Developed Python package for parameterized tensor network contraction. Investigated computational cost to classically evaluate QAOA circuit expectation values via tensor network contraction. Employed via KBR.


## Education
### Bachelor of Arts - BA in Data Science, Physics
University of California, Berkeley

### Davis Senior High School


## Contact & Social
- LinkedIn: https://linkedin.com/in/glenn-leblanc
- Portfolio: https://ocf.berkeley.edu/~gln

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Source: https://flows.cv/glennleblanc
JSON Resume: https://flows.cv/glennleblanc/resume.json
Last updated: 2026-04-13