Working on the AI and Data Science teams in Engineering at Citrine offers the rare 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: Assessing the Frontier: Active Learning, Model Accuracy, and Multi-objective Materials Discovery and Optimization (2019). at https://arxiv.org/abs/1911.03224 Can machine learning identify the next high-temperature superconductor? Examining extrapolation performance for materials discovery (2018). at https://doi.org/10.1039/C8ME00012C Overcoming data scarcity with transfer learning. (2017). at https://arxiv.org/abs/1711.05099 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
Projects you’ll work on
- The next-generation platform for empowering scientists with Citrine’s AI, guiding experimental design to accelerate discovery and lead to research breakthroughs.
- A system for sharing and managing materials data across an enterprise’s researchers, with the goal of fostering collaboration between scientists, reducing experimental waste, and aiding in the management of R&D projects.
- Complex analysis &visualizations that allow our users to gain deeper insights into their data.
What You’ll Do
- Build backend services to support product features on the Citrine Platform that puts our core technology in the hands of scientists
- Deploy and support your software &infrastructure in production
- Collaborate closely with other engineers, frequently reviewing code and discussing architecture
- Mentor other developers
- Design high-performance, scalable systems
- Test &analyze the impact and performance of your software
- Work in a multi-functional team on features from concept to delivery
The Stack
- Scala, Python
- Swagger/OpenAPI
- PostgreSQL, Redis, AWS DynamoDB
- Elasticsearch
- AWS Computer Services (EC2, ECS, Fargate, Batch)
Skills and Qualifications
- BS in Computer Science or similar technical field of study, or equivalent industry experience
- 5 years of experience writing production software in Java or Scala
- Experience building backend web services
Nice-to-haves
- Familiarity with Akka, Slick, and basic functional programming
- Familiarity with containerization / Docker
- Experience with AWS
- Experience with non-relational database such as DynamoDB
- Experience with production monitoring systems such as DataDog