Data & AI Research Engineering (DARE) is a uniquely interdisciplinary team working at the intersection of materials science, machine learning, and software engineering. We are responsible for researching, developing, testing, implementing, and maintaining the core materials-aware machine learning functionality that powers the Citrine Platform. We collaborate extensively across the company — other teams rely on us throughout the product lifecycle to translate ideas to math to code and back again. Example projects: Improve and maintain our core Python libraries that enable our users to apply machine learning to solve the world’s most important materials science problems at an industrial scale Collaborate with our Product team to shape the future of our AI capabilities and support our customer’s unique use cases Improve the interpretability of machine learning models and develop tools to communicate that information to users Improve our inverse design capabilities that efficiently explore complex parameter spaces that characterize real-world materials synthesis problems Collaborate with our External Research and Development (ERD) team to write and publish papers related to the work we’re doing Develop new methods to quantify uncertainty in machine learning predictions
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Job Type
Full-time
Career Level
Mid Level