Scientific Computing Jobs in Missouri (NOW HIRING)

About SLAC National Accelerator Laboratory

SLAC National Accelerator Laboratory is a U.S. Department of Energy laboratory operated by Stanford University. For over 60 years, SLAC has been at the forefront of scientific discovery, exploring how the universe works at the biggest, smallest, and fastest scales. From particle physics to astrophysics, materials science to biology, SLAC's world-class research facilities and scientific expertise drive innovation and push the boundaries of human knowledge.

Do you enjoy collaborating with a diverse group of people to solve complex challenges? Does contributing to breakthrough discoveries in science and working in a world-leading research environment excite you?

The Application and User Services (AUS) group is seeking an energetic, forward-thinking software engineer to develop tools and workflows for science projects such as the Vera C. Rubin Observatory US Data Facility, hosted at SLAC. You will work with a team that supports multipleglobal, open-science, collaborations eager to leverage cutting-edge, best-in-class computing, platform and data services. We continually explore new platforms and technologies, and you will have a direct hand in shaping what the future of scientific computing at SLAC looks like.

S3DF is SLAC's centralized scientific computing facility, providing unified high-performance computing, storage, and data services to a broad portfolio of science programs. Current users include the Vera C. Rubin Observatory US Data Facility (supporting the Legacy Survey of Space and Time), LCLS (the Linac Coherent Light Source X-ray free-electron laser), ATLAS and other HEP experiments, and a growing number of additional programs. These experiments collectively generate and manage data at petabyte scale, with demanding requirements for throughput, reliability, and scientific reproducibility.

You will design, implement, and support the applications and APIs used to process, manage, and serve scientific data across these programs. You will contribute to troubleshooting and tuning the full portfolio of services used by scientists worldwide. You will have experience in data-intensive workflows and containerization and deployments on Kubernetes clusters. Some of your code will interface with authentication and authorization frameworks, so familiarity with Identity and Access Management (IAM) concepts is a plus.

A significant and growing part of this role will involve scientific data management at scale. The Facility manages a complex, multi-system data landscape spanning distributed data repositories, metadata catalogs, and data access layers. You will help us bring coherence, reliability, and formal stewardship practices to this environment: aligning data lifecycle policy with operational reality, ensuring metadata integrity, and building the tooling and workflows that let us manage data responsibly across its full lifetime.

We encourage open dialog, free thinking, cooperation, and a growth mindset. This is an opportunity to learn, enable groundbreaking science, and develop your skills in a uniquely collaborative scientific computing environment.

• Design, implement, and maintain applications and APIs for S3DF science programs, enabling scientists worldwide to access, process, and analyze large-scale experimental and observational datasets
• Build and improve data-serving interfaces and processing pipelines that handle petabyte-scale astronomical datasets
• Containerize applications and deploy them on Kubernetes clusters, following modern cloud-native best practices
• Participate in design and development of software tools for scientific data management and data processing, with assignments varying according to experiment priorities and lifecycles.
• Integrate applications with Identity and Access Management frameworks (OIDC, SAML2, JWT, LDAP, COManage, etc.) to ensure secure and appropriate data access
• Write clean, well-tested, well-documented code; contribute to and maintain shared software repositories across S3DF science programs

• Contribute to the integration and reconciliation of the Rubin data access layer with distributed data management systems (including Rucio), ensuring consistent views of datasets across systems
• Help develop and implement data lifecycle policies defining how datasets are created, retained, migrated, and retired across storage tiers in alignment with scientific and operational requirements
• Work on tooling for metadata integrity and remediation : detecting inconsistencies between catalogs, registries, and physical storage, and building workflows to detect and resolve them
• Contribute to formalizing levels of data stewardship responsibility by dataset type clarifying ownership, curation standards, and ac