Responsibilities
- Develop and refine deep learning models tailored to scientific data types within the Large Spectral Model framework.
- Lead end-to-end machine learning initiatives, from experimental design through evaluation and iterative improvement.
- Produce high-quality, tested code in PyTorch and NumPy to support rapid experimentation.
- Keep informed on advancements in deep learning as they apply to chemistry and biology.
- Suggest and build prototypes for novel approaches to improve modeling performance.
- Collaborate with cross-functional teams of scientists and engineers to embed models into products and systems.
Work Arrangement
Hybrid
