Davis Blalock
Research Scientist at Google DeepMind
San Francisco, California, United States
Summary
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RockstarDavis Blalock is a research scientist at MosaicML with an MIT PhD and 11 years of experience, based in San Francisco. He focuses on building fast machine learning algorithms and low-level infrastructure, contributing to projects like bolt that target 10x faster matrix and vector operations. His work spans C++ and build-system integrations (Bazel, Python packaging) as well as model development and training frameworks, adding things like a ResNet-9 to Composer. He also improves developer experience and CI/CD for large ML repos, having added linters, pre-commit hooks, and Makefile automation to LLM-Foundry. That blend of rigorous research and pragmatic tooling lets him move ideas from efficient kernels to reproducible, production-ready training pipelines.
11 years of coding experience
12 years of employment as a software developer
Github Skills (31)
pytorch10
github-ci10
gnu-make10
c-language10
integrate10
python10
model-driven10
github-actions-workflows10
machine-learning10
build-system10
makefile10
integrations10
model-building10
automation10
deep-learning10
Programming languages (3)
Github contributions (5)
dblalock/bolt
Feb 2017 - Jun 2022
10x faster matrix and vector operations
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 reviews, 268 commits, 4 PRs in 5 years 5 months
Contributions summary:Davis's commits primarily involve setting up and getting builds and profiling working under Bazel, including the implementation of a Python setup script. The code changes include additions to a C++ header file, suggesting the user is working with the core of the project's functionality, potentially involving matrix and vector operations. The commits demonstrate efforts to integrate build and installation processes, implying work within a development environment.
math10xcompressiondata-miningmachine-learning
mosaicml/composer
Oct 2021 - Oct 2022
Supercharge Your Model Training
Role in this project:ML Engineer
ML EngineerContributions:164 reviews, 34 commits, 52 PRs in 11 months
Contributions summary:Davis primarily contributed to the implementation and integration of machine learning models and related components within the MosaicML Composer framework. They added a new ResNet-9 model for CIFAR-10, including model definitions, configuration files, and integration with existing training pipelines. Their contributions involved modifying existing framework components, adding new model architectures, and ensuring compatibility with the testing framework, showcasing skills in deep learning model development and integration within a machine learning training library.
pytorchml-systemsdeep-learningneural-networksmachine-learning
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