Gary Linscott
Principal Software Engineer At DoorDash Labs
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolGary Linscott is a founder and seasoned software leader with 15 years of experience building AI-driven, real-world systems from startup to hyperscale. He has led motion-planning and ML teams at autonomous vehicle leaders Zoox and DoorDash Labs, and ran infrastructure and TPU work at Google, demonstrating deep expertise in JAX/PyTorch, reinforcement learning, and realtime inference. His background spans product-grade systems engineering at Microsoft and quantitative engineering at Goldman Sachs, giving him a rare blend of research-oriented ML and production systems experience. An active open-source contributor to high-performance chess engines like Stockfish and Leela Chess (notably improving core network and evaluation code), he brings attention to algorithmic detail and performance tuning. Based in Seattle, he now focuses on commercializing AI systems through his company TensorMill, applying lessons from both large tech and autonomous-vehicle research. Colleagues describe him as someone who moves fluidly between low-level optimization and high-level product strategy, often surfacing subtle algorithmic improvements that materially boost system performance.
15 years of coding experience
17 years of employment as a software developer
BSC Computer Science, BSC Computer Science at Queen's University
Stackoverflow
1,471reputation
47kreached
7answers
0questions
Github Skills (21)
algorithm10
algorithms10
c-language10
data-structure10
chess10
optmization10
performance-optimization10
optimisation10
data-structures10
cprogramming-language10
chess-engine10
optimization10
debug9
debugging9
generics6
Programming languages (6)
Github contributions (5)
glinscott/leela-chess
Jan 2018 - Jun 2018
**MOVED TO https://github.com/LeelaChessZero/leela-chess ** A chess adaption of GCP's Leela Zero
Role in this project:
Back-end Developer
Back-end DeveloperContributions:5 releases, 305 commits, 106 PRs in 5 months
Contributions summary:Gary focused on refactoring and improving the `Network.cpp` file, suggesting they are working on the core computational aspects of the project. They modified code related to initializing and processing the network, including adding code to generate and use promotion moves and incorporating Winograd transformation. The changes indicate a focus on performance optimizations and potentially a deeper understanding of the underlying machine learning model implemented in the project. The user also added a few small tweaks that don't make up significant contributions, such as those in `main.cpp`.
chess-enginegcpzerouci
mcostalba/Stockfish
Feb 2012 - Oct 2015
UCI chess engine
Role in this project:Back-end Developer
Back-end DeveloperContributions:70 commits, 1 comment in 3 years 8 months
Contributions summary:Gary primarily contributed to the chess engine's evaluation and endgame logic. Their work included implementing features for stalemate detection in specific endgame scenarios, adding penalties for undefended pieces, and optimizing existing evaluation routines. They also incorporated and tuned improvements related to pawn structure analysis and major piece activity, enhancing the engine's overall performance.
chess-engineuci-chess-enginemachine-learninguci
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