Machine Learning Research EngineerWindBorne Systems • Palo Alto, California, United States
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Machine Learning Research Engineer
WindBorne Systems
- Palo Alto, California, United States
- Palo Alto, California, United States
About
What you'd work on
Own experiments end-to-end: architecture changes, loss function design, training runs, and rigorous evaluation against operational baselines. The research direction changes when results come in, and you drive it.
Understand real-world data, then model it: dig into messy real-world datasets like severe weather events and energy market variables, then extend our foundational model to predict them.
Evaluation & scientific rigor: weather forecasting is not as simple as maximizing a Kaggle score. You'd help make sure we're actually getting better, not just overfitting to metrics.
You'd be a good fit if you:
Have trained large models from scratch. You understand distributed training, gradient dynamics, and what it feels like when a run is going sideways at step 30k.
Care about the science, not just the engineering. You've read papers to understand a problem domain, not just to replicate architectures.
Are comfortable getting your hands dirty with hardware and the failure modes of real operational systems, not just clean research problems.
Are comfortable with messy, real-world data that doesn't come in neat CSV files: satellite radiances, irregularly-spaced observations, multi-source fusion.
Can move fast without a product spec. The research direction changes when results come in, and you're energized by that.
Nice to have: Atmospheric science or physics background, experience with weather/climate data, PyTorch distributed internals, data assimilation or inverse problems.
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Languages
- English
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