Python Software Developer

Join us and make your mark on the world! Lawrence Livermore National Laboratory (LLNL) advances science and technology to strengthen U.S. security and promote global stability. Our mission spans nuclear deterrence, threat preparedness, energy security, and multi-domain defense, empowering teams to tackle today’s and tomorrow’s toughest challenges. With a culture built on innovation and operational excellence, LLNL is where your expertise can drive real impact.

About the role

We're seeking a software engineer passionate about building robust data management systems that serve as the backbone of critical scientific work. This role sits at the intersection of solid software engineering and cutting-edge AI, offering the opportunity to create elegant, scalable data solutions while pushing the boundaries of artificial intelligence. You'll work on systems where traditional engineering excellence meets the transformative potential of AI, collaborating with scientists, engineers, and domain experts to translate evolving scientific requirements into well-architected, maintainable software.

This position is within the Global Security Computing Applications Division (GS-CAD) of the Computing Directorate, matrixed to the Global Security Directorate, and offers a hybrid schedule blending in-person and virtual presence with flexibility to work from home up to 2, and at times 3, days per week.

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 of data visualization and analysis tools to assist scientists in interpreting simulation results.
• Integrate simulation and computation libraries with other platforms, applications, and data pipelines.
• Troubleshoot issues spanning 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 by 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.

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.

Qualifications We Desire

• 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.

Pay

$175,530 - $222,564 Annually. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee’s position within the salary range will be based on factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.

Benefits

• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (*depending on project needs)

Visit LLNL Values to learn more about our workplace culture.

Additional Information

This is a Career Indefinite or At Will appointment. Lab employees and external candidates may be considered for this position.

This position requires a Department of Energy (DOE) Q-level clearance. If selected, we will initiate a Federal background investigation to determine eligibility for access to classified information or matter. All L or Q cleared employees are subject to random drug testing. Q-level clearance requires U.S. citizenship. External applicants selected for this position must pass a post-offer, pre-employment drug test, which includes testing for marijuana as Federal Law applies to us as a Federal Contractor.

Depending on job duties, you may be required to work in Limited Areas where personal and/or laboratory mobile devices (e.g., cell phones, tablets, fitness devices, wireless headphones) are not permitted. Hearing aids without wireless capabilities or with wireless disabled are allowed in Limited Areas, Secure Space, and Transit/Buffer Space within buildings. Sensitive Compartmented Information Facilities require separate approval.