Scott Steinhauser
Software Engineer at Meta
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolScott Steinhauser is a software engineer based in the San Francisco Bay Area with six years of experience building performant systems at scale, currently on Meta’s engineering team. A Texas A&M CS graduate with a 4.0 GPA, he blends strong academic foundations with practical internship experience at Microsoft, Roblox, and Facebook AI. He enjoys collaborative problem solving and has applied that mindset to optimize 3D simulation performance in the high-profile Habitat-Sim project, adding modular profiling, VHACD integration, and voxelization tooling. Comfortable across backend services, data migration, and tooling, he has moved large datasets, automated workflows, and prototyped PowerApps and CDS integrations. Known for curiosity and rapid learning, he gravitates toward challenging engineering problems that deliver practical value to teams and users.
6 years of coding experience
1 year of employment as a software developer
Bachelor of Science - BS, Computer Science, 4.0, Bachelor of Science - BS, Computer Science, 4.0 at Texas A&M University
Github Skills (11)
simulations10
simulation10
c-language10
physics10
cprogramming-language10
performance-optimization10
python10
simulator10
computer-vision9
3d-graphics8
ai8
Programming languages (3)
Github contributions (5)
facebookresearch/habitat-sim
Feb 2021 - Apr 2021
A flexible, high-performance 3D simulator for Embodied AI research.
Role in this project:
ML Engineer & Performance Engineer
ML Engineer & Performance EngineerContributions:26 reviews, 109 commits, 12 PRs in 2 months
Contributions summary:Scott's contributions focus on enhancing the performance of the physics simulation within the Habitat-Sim environment. They implemented a modular profiling system for testing changes to the core simulation, as evidenced by the `physics_benchmarking.py` file modifications. Further contributions involve the integration of VHACD for accelerating collision detection and a voxelization framework for creating boundary grids and mesh visualizations, demonstrating skills in optimizing 3D simulations and related data processing.
roboticsembodied-aicomputer-visionsimulation3d-simulator
ScottCSteinhauser/habitat-lab
Oct 2021 - Apr 2022
A modular high-level library to train embodied AI agents across a variety of tasks, environments, and simulators.
Contributions:2 PRs, 53 pushes, 26 branches in 6 months
simulatorsdeep-learningembodied-aireinforcement-learninghigh-level
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