Tim Sweeney
Principal Software Engineer at Weights & Biases
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolTim Sweeney is a Principal Software Engineer based in San Francisco with 11 years of experience building ML infrastructure and developer tooling. He combines hands-on back-end and ML engineering at Weights & Biases with product leadership experience running internal ML platforms at Twitter and enterprise search at Workday. Tim’s work bridges research and production—he’s shipped integrations that convert matplotlib plots to Plotly within the widely used wandb platform, improving robustness for plot generation and test coverage. Comfortable navigating cloud data stacks (GCP/BigQuery), TensorFlow/TFX pipelines, and orchestration tools, he focuses on making systems that help people iterate faster. He holds an MS in Computer Science (Machine Learning) from Georgia Tech and pairs data-driven product judgment with deep technical execution. Colleagues describe him as a pragmatic engineer who turns subtle edge-case bugs into durable platform improvements.
11 years of coding experience
9 years of employment as a software developer
California Polytechnic State University, San Luis ObispoMaster of Science - MS Computer Science - Machine Learning, Master of Science - MS Computer Science - Machine Learning at Georgia Institute of Technology
Github Skills (13)
matplotlib10
data-visualizations10
data-visualization10
data-visualisation10
python10
plotly10
testing10
deep-learning8
pytorch8
experiment8
keras8
tensorflow8
data-science7
Programming languages (6)
Github contributions (5)
wandb/wandb
Oct 2020 - Jan 2023
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:277 reviews, 352 commits, 232 PRs in 2 years 3 months
Contributions summary:Tim's contributions centered on enhancing the codebase to support and integrate with matplotlib plots. They implemented conversions from matplotlib plots to Plotly format and added the related dependency. The user also enhanced the test suite, added helper functions, and implemented implicit conversion from pyplot objects. Their work addressed a bug regarding plots without data, improving the handling of plot generation within the platform.
pythoncollaborationtensorflowhyperparameter-tuningcli
wandb/weave
Jun 2023 - Apr 2025
Weave is a toolkit for developing AI-powered applications, built by Weights & Biases.
Contributions:25 releases, 2853 reviews, 1438 PRs in 1 year 10 months
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