Gabriel Hackebeil
Senior Algorithms Engineer at Tesla
San Francisco, California, United States
Summary
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Rockstar🎓
Top SchoolGabriel Hackebeil is a Senior Algorithms Engineer based in San Francisco with 12 years of experience designing and shipping optimization and mathematical-programming solutions across startups and high-growth companies. He holds dual master’s degrees in Operations Research and Computer Science and a background in chemical engineering and mathematics, which informs his multi-disciplinary approach to algorithm design. Gabriel led optimization teams at Geli and now develops algorithmic systems at Tesla, focusing on solver integration, conic constraints, and robust handling of variable bounds in production solvers. As a core contributor to Pyomo he extended its parallel stochastic and nonlinear capabilities and fixed cross-solver inconsistencies—work that bridges research-grade modeling and production reliability. Known for turning advanced mathematical constructs into pragmatic implementations, he combines HPC-aware thinking with hands-on back-end development and data science. Outside of product work he brings a quietly systematic curiosity, often surfacing subtle solver-edge cases before they affect production.
12 years of coding experience
6 years of employment as a software developer
Master's degree, Operations Research, Master's degree, Operations Research at University of MichiganMaster’s Degree, Computer Science, Master’s Degree, Computer Science at Oregon State UniversityBachelor’s Degree, Chemical Engineering, Bachelor’s Degree, Chemical Engineering at Texas A&M University
Stackoverflow
1,416reputation
84kreached
56answers
1question
Github Skills (17)
python10
pyomo10
mathematical10
nonlinear-programming10
linear-programming10
modeling10
optimization10
data-structure9
algorithm9
algorithms9
test-automation9
data-structures9
recursion6
ipopt6
nonlinear-optimization6
Programming languages (6)
Github contributions (5)
Pyomo/pyomo
Oct 2014 - Feb 2021
An object-oriented algebraic modeling language in Python for structured optimization problems.
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:2 reviews, 1877 commits, 100 PRs in 6 years 5 months
Contributions summary:Gabriel's contributions focused on modifying and extending the core functionality of the Pyomo library, specifically within the areas of mathematical programming and optimization. The commits demonstrate expertise in integrating and manipulating mathematical expressions, which included adding and testing functionalities related to conic constraints, handling variable bounds within solvers, and supporting the integration of new mathematical constructs. The user's efforts also involved resolving bugs and ensuring consistent behavior across various solver interfaces, highlighting a strong understanding of the library's underlying structure.
pythonnonlinear-programmingstructuredgurobiproblems
ghackebeil/gjh_asl_json
Apr 2016 - Oct 2022
Contributions:2 reviews, 39 commits, 2 PRs in 6 years 7 months
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