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Research Scientist, Distributed Workflows

Job in Oak Ridge, Anderson County, Tennessee, 37830, USA
Listing for: Oak Ridge National Laboratory
Full Time position
Listed on 2026-07-15
Job specializations:
  • Software Development
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below

Overview

Oak Ridge National Laboratory (ORNL) is seeking a Research Scientist to advance distributed workflow orchestration and cross‑facility integration in support of the Genesis Mission, the American Science Cloud, and the Oak Ridge Leadership Computing Facility (OLCF). Working within the Workflows and Ecosystem Services (WES) Group at the National Center for Computational Sciences (NCCS), you will design and deploy APIs, service meshes, and workflow orchestration systems that bridge leadership computing resources, instruments, and cloud platforms.

You will collaborate with scientists, facility operators, and DOE laboratory partners to lower barriers to scalable, automated scientific computing.

WES designs and implements workflow, data, and ecosystem technologies that enable reliable, automated execution of scientific applications across heterogeneous, geographically distributed computing environments, integrating compute, storage, networking, and visualization resources into cohesive, end‑to‑end systems.

The WES Group sits within the Advanced Technologies section of the National Center for Computational Sciences (NCCS), a division of the Computing and Computational Sciences Directorate (CCSD) S provides state‑of‑the‑art computational and data science infrastructure for technical and scientific professionals and hosts the Oak Ridge Leadership Computing Facility (OLCF), a DOE Office of Science User Facility that is home to Frontier, the first supercomputer to break the exascale barrier.

NCCS staff work at the forefront of leadership computing, enabling scientific discovery for researchers across government, academia, and industry.

Responsibilities
  • Distributed Workflow Orchestration:
    Architect, implement, and operate cross‑facility workflow orchestration systems that integrate job schedulers (e.g., SLURM), data movement services (e.g., Globus), and computing endpoints across multiple DOE facilities. Design execution patterns that support autonomous experimentation, multi‑facility data pipelines, and event‑driven automation.
  • API and Service Mesh Development:
    Design and implement RESTful APIs and service meshes that expose OLCF computing resources to diverse scientific workflows and external facilities. Define API specifications, manage versioning, and guide systems from prototype through production deployment.
  • Genesis Mission / American Science Cloud Integration:
    Lead ORNL's technical engagement with the Genesis Mission, architecting cross‑facility workflow and data infrastructure that connects leadership computing, experimental facilities, and cloud platforms in support of DOE's vision for integrated science. Drive contributions to the American Science Cloud (AmSC) by designing and deploying interoperable APIs, data movement services, and orchestration layers that enable seamless scientific workflows across the DOE complex.

    Coordinate with partner laboratories and facilities (e.g., ANL, NERSC) to align interfaces and standards, and establish ORNL/OLCF as a foundational compute and data hub within the emerging national science infrastructure.
  • Agentic Workflow Design and Autonomous Control Systems:
    Design and implement agentic workflow architectures that enable autonomous, closed‑loop scientific experimentation across HPC and instrument facilities. Develop LLM‑integrated orchestration layers, tool‑use pipelines, and event‑driven control systems that allow AI agents to plan, execute, monitor, and adapt multi‑step scientific workflows with minimal human intervention. Apply agentic patterns to use cases such as autonomous materials discovery, self‑steering simulations, and adaptive experimental campaigns, in coordination with domain scientists and facility operators.
  • Scientific Domain Support:
    Collaborate with domain scientists in areas such as climate science, materials science, and autonomous experimentation to translate research objectives into scalable, automated workflow solutions. Provide documentation, training, and direct user support.
  • Scripting and Tooling:
    Develop command‑line tools and automation in Python, Bash, and/or C/C++ to encapsulate workflow steps, manage configuration files (e.g.,…
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