Data and Artificial Intelligence Research Engineer (DARE)
Redwood City, CA / Remote /
Technology – Engineering /
Design and build the core scientific libraries that enable our users to apply machine learning to solve the world’s most important materials science problems at an industrial scale.
At Citrine, we’re changing the way new materials are developed.
We are the industry leader in materials informatics, the application of data-driven methods to materials and chemicals development. Our platform provides data management and AI tools that help our customers rapidly develop better, more sustainable materials. Our users are scientists and engineers at huge manufacturing and materials companies, and researchers at leading universities and government labs. Our platform enables our users to accelerate the development of new materials.
In 2020 Citrine was recognized for technology innovation by the Global CleanTech Group and was named one of the most promising AI startups by CB Insights. As a team, we are ambitious with our goals, passionate about our vision, and eager to grow and learn from each other. Our team is growing fast and looking for the best to join us.
Though our technology was originally built by materials scientists, our team now consists of professionals trained in a diverse set of fields, including data science, physics, biology, and computer science. We have offices in the San Francisco Bay Area, Chicago, and Pittsburgh, and our customers include Fortune 1000 materials and product companies.
About the Role
Data & AI Research Engineering (DARE) is a uniquely interdisciplinary team working at the intersection of materials science, applied mathematics, and software engineering. We are responsible for researching, developing, testing, and implementing scientific methods that form 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 include:
- Improve the interpretability of machine learning models and develop tools to communicate that information to users
- Develop ways to efficiently explore the complex parameter spaces that characterize real-world materials synthesis problem
- Build tools that allow users to express their scientific knowledge through custom graphical models
- Develop new methods to quantify uncertainty in machine learning predictions
Working at Citrine offers the opportunity to collaborate with applied scientists at the leading edge of statistical learning theory and application.
Here are a few representative peer-reviewed publications describing research done at Citrine in support of the platform’s AI capabilities:
Hutchinson, M., Antono, E., Gibbons, B. et al. Overcoming data scarcity with transfer learning. (2017). at https://arxiv.org/abs/1711.05099
Ling, J., Hutchinson, M., Antono, E. et al. Integr Mater Manuf Innov. High-Dimensional Materials and Process Optimization Using Data-Driven Experimental Design with Well-Calibrated Uncertainty Estimates. (2017). at https://doi.org/10.1007/s40192-017-0098-z
Skills and Qualifications
- MS, PhD, or equivalent experience in the sciences, mathematics, statistics, or computer science
- Experience solving scientific problems with computational techniques (we mostly use Python and Scala/Java)
- Ability to communicate complex technical concepts and design choices
All qualified applicants will receive consideration for employment without regard to race, creed, color, or national origin.
Our Benefits (for exempt, full time employees based within the United States)
401k with matching up to 4% of salary
Medical, vision, dental insurance (we pay 100% of your premium and 75% of your dependents)
Equity options within the company
Flexible PTO on top of our 14 paid company holidays (includes your birthday!)
Free financial counseling
$250 tech allowance
$5,000 annual professional growth budget