Research Software Engineer, LINCC Frameworks (2 positions)

University of Washington•Seattle, WA

About The Position

The Department of Astronomy has an outstanding opportunity for a Research Software Engineer to join the LINCC Frameworks Team. Two Positions Available. About this Opportunity The next generation of astronomical surveys, including those scheduled to be conducted by the NSF-DOE Vera C. Rubin Observatory and the recently announced Schmidt Observatories, will provide unprecedented data sets with the potential to answer fundamental questions about the universe. At the same time, the flood of data will introduce new computational challenges. We are looking for Software Engineers to work at the intersection of state of the art computer science and cutting edge astrophysics. The engineers will design and build analysis frameworks that run on the cloud or high-performance computing (HPC) systems that can store, search, analyze and annotate data of the volume and complexity of the Rubin Observatory’s Legacy Survey of Space and Time (LSST) data. These frameworks will provide an interface for the astronomical community to run real time and batch analyses (e.g. to search for one-in-a-million events in continuous streams of data). You will shape, drive, and execute this vision to build scalable software that can help shape the future of astronomical research. As a Systems Software Engineer you will work with engineering teams at the University of Washington and Carnegie Mellon University. You will develop new cloud-based and HPC software platforms that will use cutting edge computer science techniques to enable the analysis of time series and static data from the next generation of surveys. You will work with astronomers and scientists to integrate their analysis code into these scalable analysis frameworks utilizing tools such as Spark and Dask. The majority of development will be in Python with some performance critical code in C/C++/Rust. Development will incorporate software best practices such as peer code review, to produce secure, testable, maintainable, and extensible code. You will participate in the hiring process and mentor others - improving their skills, their knowledge of your software, and their ability to get things done.

Requirements

Bachelor’s Degree, computer science or related field
A minimum of 3 years of experience in software development
1-3 years of programming experience in an industrial or academic role
Equivalent education and/or experience may substitute for minimum qualifications except when there are legal requirements, such as a license, certification, and/or registration.
Programming experience with at least one modern language such as Python, Java, C++ including object-oriented design

Nice To Haves

Experience with software design and engineering best practices such as source control and code reviews
Experience with distributed computing frameworks such as Spark or Dask
Experience developing software for cloud-based or high-performance computing (HPC) environments
Experience with performance-critical programming in C, C++, or Rust
Familiarity with astronomical data, surveys, or scientific computing workflows

Responsibilities

Software Design and Development (40%): Design, develop, and maintain scalable analysis frameworks for cloud-based and HPC systems using cutting-edge computer science techniques, enabling the astronomical community to store, search, analyze, and annotate large-scale time series and static data from LSST and the Schmidt Observatories. Primary development in Python, with performance-critical components in C, C++, or Rust.
Software Design and Development (40%): Design, develop, and maintain scalable analysis frameworks for cloud-based and HPC systems that enable the astronomical community to store, search, analyze, and annotate large-scale time series and static data from LSST and the Schmidt Observatories. Primary development in Python, with performance-critical components in C, C++, or Rust.
Scientific Integration and Collaboration (20%): Work directly with astronomers and scientists at UW and Carnegie Mellon University to understand research needs and integrate scientific analysis code into scalable frameworks, utilizing tools such as Spark and Dask.
Software Quality and Engineering Best Practices (15%): Implement and uphold software engineering best practices including peer code review, version control, testing, and documentation to produce secure, testable, maintainable, and extensible code. Perform analysis and troubleshooting for software issues and process challenges.
Problem Resolution/Project Tasks (15%): Perform analysis and troubleshooting for application issues and process challenges Responsible for the successful completion of assigned project tasks with minimum supervision
Cross-Functional Team Participation (10%): Function within cross-domain teams spanning astronomy and computer science. Contribute to team discussions aimed at advancing project goals, learn new skills and technologies as needed, and solve meaningful problems through technical innovation