Machine Learning Software Developer

About The Company

Join us and make YOUR mark on the World!

Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability.

Our mission spans four critical national security areas: nuclear deterrence, threat preparedness, energy security, and multi-domain defense. We empower teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.

About The Role

We have an opening for a Machine Learning Software Developer to contribute to groundbreaking research and development efforts. The successful candidate will focus on deriving greater knowledge from dense and sparse sensor networks operating across multiple phenomenological modalities. Additionally, you will play a key role in advancing Large Language Model-driven agents, which are designed to augment the analytical capabilities of scientific staff working in this domain.

This position is part of the Global Security's Nuclear Thread Reduction (N) Program and falls under the administrative division of the Global Security Computing Applications Division (GS-CAD) within the Computing Directorate. The role offers an exciting opportunity to work at the intersection of software engineering, machine learning, and high-performance computing in a secure and collaborative environment.

The position will be filled at either level based on the candidate's knowledge and experience, with additional responsibilities assigned if hired at the higher level. As a Machine Learning Software Developer, you will be engaged in developing innovative software solutions, collaborating across multidisciplinary teams, and contributing to projects that have a significant impact on national security and scientific advancement.

Qualifications

To qualify for this role, candidates must be able to secure and maintain a U.S. DOE Q-level security clearance, which requires U.S. citizenship. A Bachelor’s degree in computer science, machine learning, computer engineering, artificial intelligence, or a related technical field is essential, along with relevant experience or an equivalent combination of education and skills.

Fundamental knowledge in reinforcement learning, Large Language Model frameworks, agentic AI, or Graph Neural Networks is required. Familiarity with the software development lifecycle—including requirements gathering, documentation, feature implementation, and testing—is necessary. Experience developing software for High-Performance Computing (HPC) environments and working with systems such as Flux or SLURM is highly desirable.

Proficiency in programming languages such as Python, C++, or JAVA within Linux, UNIX, and Windows environments is essential. Strong verbal and written communication skills are necessary for effective collaboration and technical presentation.

At the SES.2 level, candidates should possess a Master’s degree or higher, along with the ability to independently manage multiple technical tasks, adapt to changing priorities, and communicate complex technical information effectively to diverse audiences. Broader experience in multi-modal data collection, agentic AI/ML, Model-Context-Protocol (MCP), and LLM integrations is advantageous.

Responsibilities

• Contribute to the development of software applications using object-oriented analysis, design, and programming techniques, primarily in Python.
• Support multidisciplinary teams under general direction, employing industry-standard software development practices and modern programming languages.

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• Design, develop, and optimize Large Language Model-centric applications, including scientific, graphical user interface, database, and visualization tools on Windows and UNIX platforms.
• Participate in all phases of the software development lifecycle—from requirements analysis and design to implementation, debugging, testing, and deployment.
• Perform independent analysis to solve broadly defined and moderately complex problems, providing effective solutions aligned with project goals.
• Contribute to project planning, technical documentation, and code reviews to ensure high-quality software delivery.
• Collaborate with scientific and technical staff to understand requirements and translate them into functional software solutions.
• Maintain awareness of emerging technologies in machine learning, AI, and high-performance computing to continuously improve project outcomes.
• Perform additional duties as assigned, supporting the overall mission of the organization.
  
  

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Benefits

Lawrence Livermore National Laboratory offers a comprehensive benefits package designed to support employee well-being and professional growth. Employees are eligible for a flexible benefits package, including health, dental, and vision insurance, as well as a 401(k) retirement plan with company matching contributions. The Laboratory also provides education reimbursement programs, relocation assistance, and flexible scheduling options based on project needs.

Additional perks include access to wellness programs, employee assistance programs, and opportunities for continuous learning and development. The Laboratory’s commitment to fostering an inclusive and innovative work environment ensures employees can thrive professionally and personally.

Equal Opportunity

Lawrence Livermore National Laboratory is an equal opportunity employer committed to creating a diverse and inclusive work environment. We consider all qualified applicants without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.

We are dedicated to providing reasonable accommodations to support candidates throughout the application and interview process. Our goal is to ensure a fair and accessible recruitment experience for all applicants.