Scientific Systems Software Developer
Listed on 2026-05-30
-
Software Development
Data Scientist, Data Engineer, Software Engineer
Software Developer 2
SLAC National Accelerator Laboratory is a U.S. Department of Energy laboratory operated by Stanford University.
AboutThe Role
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 will work with a team that supports multiple global, 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 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.
Key Responsibilities – Application Development & Integration- 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 life cycles
- 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…
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).