Machine Learning Software Developer

Company Description

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 empowering 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.

We have an opening for a
Machine Learning Software Developer
to help to shape research and development efforts to derive greater knowledge from dense and sparse sensor networks operating across multiple phenomenological modalities. You will also contribute to the maturation of Large Language Model-driven agents, which work to augment the analytical capabilities of scientific staff working on this area. This position is programmatically in Global Security's Nuclear Thread Reduction (N) Program and administratively in the Global Security Computing Applications Division (GS-CAD) within the Computing Directorate.

This position will be filled at either level based on knowledge and related experience as assessed by the hiring team. Additional job responsibilities (outlined below) will be assigned if hired at the higher level.

In this role, you will

• Contribute to the development of software applications using object-oriented analysis, design, and programming techniques in Python.
• Under general direction, provide computer science, machine learning, or software development support to multitalented teams using industry standard software development practices, modern programming languages, and operating systems.
• Contribute to the development of a range of Large Language Model (LLM) centric applications including scientific, graphical user interface, database, and visualization applications on Windows and/or UNIX platforms.
• Participate in the requirements definition, analysis, design, implementation, debugging, testing, and optimization of computer programs on workstations.
• Perform other duties as assigned.

Additional job responsibilities, at the SES.
2 level

• Work independently, under limited direction, in all phases of the software development lifecycle, including design, implementation, and deployment of new features within both existing and new applications.
• Provide solutions to broadly defined and moderately complex problems through independent analysis, practical problem-solving, and effective execution.
• Contribute to the design, implementation, and deployment, ensuring alignment with project requirements, technical standards, and operational goals.

• Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
• Bachelor's degree in computer science, machine learning, computer engineering, artificial intelligence or related technical field, or an equivalent combination of technical education and relevant experience.
• Fundamental knowledge with development of Reinforcement learning, LLM frameworks, agentic AI, or Graph Neural Networks.
• Familiar with the software development life cycle, including activities such as requirements gathering, preparing documentation, implementing features, and testing code.
• Familiar with developing software for High-Performance Computing (HPC) environments and interacting with HPC systems such as job scheduling tools like Flux or SLURM.
• Fundamental knowledge developing software with Python, C++ or JAVA within Linux, UNIX, and/or Windows environments.
• Sufficient verbal and written communication skills necessary to collaborate effectively in a team environment and present and explain technical information.

Additional qualifications at the SES.
2 level

• Master's degree in computer science, machine learning, computer engineering, artificial intelligence or related field, or an equivalent combination of technical education and relevant experience.
• Ability to effectively manage concurrent technical tasks with competing priorities, along with the demonstrated ability to effectively change focus when necessary.
• Proficient verbal and written communication skills to communicate comprehensive knowledge effectively across multi-disciplinary teams and to non-technical experts, and advise senior management and/or external sponsors, and interpersonal skills necessary to effectively collaborate in a team environment.
• Broad experience in and comprehensive knowledge of multi-modal data collection, agentic AI/ML, Model-Context-Protocol (MCP), or other LLM integrations

Qualifications We Desire

• PhD with significant focus in computer science, computer engineering, AI/ML, or a related technical field.
• Knowledge of one or more of the following computer science disciplines: embedded systems, scientific data analysis, machine learning, systems programming, software engineering, or high-performance…