Andrew Tulloch
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolAndrew Tulloch is a machine learning systems engineer and founder with 14 years of experience building high-performance ML infrastructure, currently co-founding Thinking Machines Lab in San Francisco. A former Distinguished Engineer at Meta and Member of Technical Staff at OpenAI (working on GPT-4o/4.5 pretraining and o-series reasoning), he has a track record of delivering low-level, hardware-aware optimizations across PyTorch, Caffe2, TVM and FBGEMM — from C and CUDA speedups in torch/nn to quantized inference kernels. He pairs deep academic credentials (PhD-level work in statistics and ML at UC Berkeley plus advanced degrees from Cambridge and Sydney) with pragmatic engineering: fixing memory/thread-safety bugs, adding LLVM verifier hooks, and modernizing NNPACK bindings. Less obvious from his titles, he started in structured finance at Goldman Sachs, giving him a rare mix of quant finance insight and systems-level ML production expertise.
14 years of coding experience
13 years of employment as a software developer
Doctor of Philosophy (PhD), Statistics, Machine Learning, Doctor of Philosophy (PhD), Statistics, Machine Learning at University of California, BerkeleyMaster of Mathematical Statistics, Statistics, Machine Learning, Distinction (Top Grade), Master of Mathematical Statistics, Statistics, Machine Learning, Distinction (Top Grade) at University of CambridgeThe University of SydneyTER: 99.95, TER: 99.95 at Christ Church Grammar School, Claremont
Stackoverflow
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Github Skills (39)
unit-testing10
pytorch10
caffe10
c-language10
fba10
emm10
llvm10
gpu-programming10
machine-learning10
kernel10
lua10
deep-learning10
f10
performance-optimization10
ai10
Programming languages (16)
Github contributions (5)
facebookarchive/caffe2
Nov 2016 - Feb 2018
Caffe2 is a lightweight, modular, and scalable deep learning framework.
Role in this project:
ML Engineer
ML EngineerContributions:130 commits, 1 PR, 6 comments in 1 year 2 months
Contributions summary:Andrew made several contributions related to the Caffe2 deep learning framework. These involved fixing issues related to memory management, thread safety, and performance optimization within core operators and related test code. The user also implemented a new operator and addressed issues in the ARM_NEON codepaths, demonstrating a focus on improving the framework's functionality and efficiency. They further improved the performance of instance normalization for NCHW format.
pytorchscalablecaffe2deep-learningml
facebookarchive/fblualib
Oct 2014 - Jul 2015
Facebook libraries and utilities for Lua
Role in this project:Back-end Developer
Back-end DeveloperContributions:12 commits in 8 months
Contributions summary:Andrew primarily contributed to bug fixes and enhancements within the Facebook Lua library. Their work involved addressing lint warnings, fixing unused variables, and resolving issues in the LuaUnit testing framework. The user also implemented a `defaultdict` functionality and debugged the fbpython bridge. They demonstrated proficiency in Lua and familiarity with testing methodologies and code optimization.
luafacebook
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