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 secure software and firmware used in systems critical to our national security, including industrial control systems, in partnership with the Federal government, manufacturers, and asset owners and operators. You will also lead or contribute to the creation of Large Language Model-driven agents, which work to better understand supply chain threats to critical systems and networks. These positions are programmatically in Global Security’s Energy and Homeland Security (E) 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.

This position offers a hybrid schedule, blending in-person and virtual presence. You will have the flexibility to work from home one or more days per week.

You will

• Design, implement, deploy, and maintain software systems using object-oriented analysis, design, and programming techniques in Python.
• Provide computer science, machine learning, or software development support to multitalented teams using industry standard software development practices, modern programming languages, and operating systems.
• Develop a range of LLM applications including scientific, graphical user interface, database, and visualization applications on 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.3 level 

• Guide the development of novel software, firmware, and malware analysis tools leveraging LLM design strategies to better understand and mitigate threats to operational technology such as industrial control system malware.
• Identify new applications and opportunities for and help create vision and technical direction for software capabilities for critical networks and infrastructure cybersecurity working with LLNL’s program leadership.
• Develop new program growth opportunities through interactions with existing and potential sponsors and the development of research proposals.
• Develop, drive, propose, and execute new ideas and approaches to meet existing and potential sponsor needs in order to attract and retain projects, programs, and funding.

• 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 field, or an equivalent combination of technical education and relevant experience.
• Experience with development of Reinforcement learning, Large Language Model frameworks, agentic AI, or Graph Neural Networks.
• Experience in all aspects of software project life cycle: feasibility, requirements, design, implementation, integration, test and deployment.
• Broad experience developing software with either Python, C++ or JAVA within Linux, UNIX, and/or Windows environments.
• 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-cyber experts, and advise senior management and/or external sponsors, and interpersonal skills necessary to effectively collaborate in a team environment.

Additional qualifications at the SES.3 level

• Significant project leadership experience and ability to apply, lead and develop cutting-edge principles and research, working independently while effectively managing concurrent technical tasks with competing priorities.
• Significant experience creating technical directions and vision, writing research proposals, and securing sponsor funding.
• Significant experience in and knowledge of at least one of the following subject areas:
  • Data collection techniques
  • Leading software engineering projects from architecture to maintenance
  • AI/ML agentic, MCP, or other LLM integrations
  • AI Model poisoning
  • OT/IoT system design, attack vectors, or hardening techniques
• Advanced verbal and written communication skills necessary to present technical information, provide technical guidance, and interact effectively with management and external sponsors.

Qualifications We Desire

• Advanced degree with significant focus in cybersecurity, computer science, information technology, computer engineering, AI/ML, or a related field.
• Knowledge of one or more of the following computer science disciplines: embedded systems, scientific data analysis, machine learning, systems programming, software engineering, formal verification methods, industrial control systems, or high-performance computing.
• Ability to secure sponsor funding through winning proposals and sponsor relationships. Previous experience working Department of Energy, Department of Homeland Security, Department of Defense, a utility, manufacturing, or hardware/software company, or a cybersecurity firm.

Pay Range

$146,340 - $185,544 Annually for the SES.2 level 

$175,530 - $222,564 Annually for the SES.3 level

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 several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.

#LI-Hybrid

Position Information

This is a Flexible Term appointment, which is for a definite period not to exceed six years.  If final candidate is a Career Indefinite employee, Career Indefinite status may be maintained (should funding allow).

Why Lawrence Livermore National Laboratory?

• Included in 2026 Best Places to Work by Glassdoor!
• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (*depending on project needs)
• Our values - visit https://www.llnl.gov/inclusion/our-values

Security Clearance

This position requires a Department of Energy (DOE) Q-level clearance.  If you are selected, we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. Also, all L or Q cleared employees are subject to random drug testing.  Q-level clearance requires U.S. citizenship. 

Pre-Employment Drug Test

External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

Wireless and Medical Devices

Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession.  This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.  

If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas.  Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.

How to identify fake job advertisements

Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under “Find Your Job” of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.

To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf

Equal Employment Opportunity

We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment 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.

Reasonable Accommodation

Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory.  If you need a reasonable accommodation during the application or the recruiting process, please use our online form to submit a request. 

California Privacy Notice

The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.