Carey Phelps is a product leader with eight years of experience building developer tools and ML workflows, currently shaping product strategy at Resolve AI after scaling Weights & Biases from early product-market fit to enterprise adoption. At W&B they launched dataset and model versioning, hyperparameter tuning, and a model registry adopted by 100+ teams, and grew the user base to 120,000 contributing to a unicorn valuation. Carey blends product, design, and documentation ownership with hands-on ML engineering—contributing code and tutorials to the popular wandb examples that improve metric accuracy and reproducible experiments. Comfortable working with researchers, engineers, and enterprise buyers, they have a track record of hiring and leading cross-functional teams to ship developer-facing workflows. Their background in healthcare analytics and classroom-facing UX design gives them a pragmatic edge in translating complex technical needs into usable products.
8 years of coding experience
7 years of employment as a software developer
Computer Science, Computer Science at Stanford University
Example deep learning projects that use wandb's features.
Role in this project:
ML Engineer
Contributions:3 reviews, 42 commits, 15 PRs in 1 year 11 months
Contributions summary:Carey primarily focused on improving the accuracy and logging of metrics for a PyTorch CNN model used in the `pytorch-cnn-fashion` example. Their contributions included adjustments to accuracy calculations and output precision. Additionally, the user added a tutorial folder and modified the configuration for a sweep-tutorial to classify clothing items.
Contributions:11 commits, 5 pushes in 1 year 10 months
biasesweights
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