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Spectral Labs is building foundation models for engineering physical systems in San Francisco. We seek a research engineer who turns ideas into experiments and experiments into deployable models for real CAD data, using Python and PyTorch or JAX.
Role is fully in-person at our SF office with strong growth and collaboration across disciplines. You bring 0–2 years of experience, a solid understanding of why runs diverge, and a passion for making an impact regardless of background.
Spectral Labs is building foundation models for engineering physical systems. We're looking for research engineers to turn research ideas into experiments, and experiments into models that work on real CAD data: implementing architectures and training recipes, scaling distributed training, building evaluation harnesses, and designing how geometry becomes model input. You bring 0-2 years of experience building and training deep learning models, strong Python and PyTorch or JAX skills, and the fundamentals to understand why a run diverged, not only that it did. We're excited about people who can make an impact, whatever their background.
This is a fully in-person role at our office in SF. Compensation and equity total $150-250k annually. We sponsor visas end-to-end, and benefits include health insurance (with a 100%-premium option), dental, a 401(k) match, and company-expensed meals and commuting.