Python Software Developer

LLNL•Livermore, CA

1d•Hybrid

About The Position

Lawrence Livermore National Laboratory (LLNL) is seeking a Python Software Engineer to design and develop discrete and continuous scientific simulation software supporting complex industrial and physics-based modeling efforts. This role sits at the intersection of software engineering and scientific computing, working across projects at varying stages of maturity — from early prototypes to production-grade tools. You'll work closely with scientists, engineers, and domain experts to translate evolving scientific requirements into robust, well-architected, and maintainable software. This position is within the Global Security Computing Applications Division (GS-CAD) of the Computing Directorate, matrixed to the Global Security Directorate. This position offers a hybrid schedule, blending in-person and virtual presence. You will have the flexibility to work from home up to 2, and at times 3, days per week.

Requirements

Ability to secure and maintain a U.S. DOE Q-level security clearance, which requires U.S. citizenship.
Bachelor’s degree in computer science, software engineering, or a related technical discipline, or an equivalent combination of education and relevant experience.
Advanced knowledge of and hands-on experience with Python, including scientific computing libraries (e.g., NumPy, SciPy, pandas).
Advanced object-oriented design and implementation skills, with experience architecting maintainable, extensible codebases.
Demonstrated experience applying solid software engineering practices, such as, clean code, testing discipline, documentation, and code review, to build scalable and secure software.
Advanced experience with Git or an equivalent modern version control system.
Ability to work independently on ambiguous or complex problems, exercising sound technical judgment, taking initiative to develop effective solutions, and documenting designs.
Advanced written and verbal communication skills, necessary to effectively collaborate in a team environment and present and explain complex technical information and provide advice to management.

Nice To Haves

Master’s degree in computer science, computer engineering, or a related technical field.
Experience with C/C++, particularly for performance-critical or legacy scientific code integration.
Familiarity with scientific/numerical modeling concepts (e.g., differential equations, discrete-event simulation, or physics-based simulation).
Experience with HPC job schedulers (e.g., Slurm) or parallel/distributed computing.
Experience with data visualization frameworks (e.g., Matplotlib, Plotly, VTK, ParaView).
Experience with CI/CD pipelines and containerized deployment (Jenkins, Docker, Kubernetes).
Experience working in a national lab, DOE, or other regulated/classified research environment.

Responsibilities

Guide the completion of projects and contribute to the design, development, test, maintenance, and deployment of scientific computation and simulation libraries and tools.
Support multiple deployment pathways, including desktop, containerized, and HPC/cluster environments.
Contribute to the design and build data visualization and analysis tools to assist scientists interpret simulation results.
Integrate simulation and computation libraries with other platforms, applications, and data pipelines.
Troubleshoot issues that span software, computational methods, and scientific/engineering domains.
Collaborate with multidisciplinary teams including scientists, engineers, and other developers to gather requirements, participate in design reviews, and deliver high-quality solutions to complex problems.
Contribute to software quality assurance, including defining test strategies, reviewing test coverage, and ensuring compliance with project and organizational software standards.
Support the transformation of conceptual and physics-based models into well-structured, extensible software as scientific understanding matures.
Perform other duties as assigned.