Senior Cyber Super Intelligence (SI) Engineer

Qualifications

• We Desire
• Ability to engage in creative and competitive proposal processes and leverage sponsor relationships to secure new funding.
• Master’s degree or PhD with significant focus in cybersecurity, computer science, computer engineering, or data science/machine learning.
• Knowledge of one or more of the following disciplines: embedded systems, scientific data analysis, systems programming, software engineering, agentic frameworks, and high-performance computing.
• Knowledge of, and experience with, one or more of the following machine learning techniques: data science, diffusion models, time series analysis, deep learning, and large language models. Experience with industrial control systems software and hardware.
• Previous experience working Department of Energy, Department of Homeland Security, Department of War, utilities, manufacturing, or a cybersecurity firm.
• Pay Range
• $175,530 - $267,060 Annually
• $175,530 - $222,564 Annually for the SES.3 level
• $210,630 - $267,060 Annually for the SES.4 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; pay will not be below any applicable local minimum wage. 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-Onsite
• Position Information
• This is a Career Indefinite position, open to Lab employees and external candidates.
• 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. Also, you must have the ability to obtain and maintain Sensitive Compartmented Information (SCI) access. 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.
• 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.
• Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
• Bachelor's degree in cybersecurity, computer science, information technology, computer engineering, or related technical field or the equivalent combination of education and related experience.
• Advanced experience leading cybersecurity and/or applied SI research efforts. Advanced experience with building systems with SI tool pipelines and frameworks.
• Experience in malware analysis, network analysis, host forensics or some combination of these skill areas and related tools.
• Ability to communicate technical information across multi-disciplinary teams and to non-cyber experts, advising policy management, and applying interpersonal skills to collaborate effectively in a team environment.
• Advanced knowledge of state-of-the-art technologies in both SI and cybersecurity.
• Advanced analytical, problem-solving, and decision-making skills to develop creative solutions to complex problems.
• Ability to effectively manage concurrent technical tasks with competing priorities, along with the demonstrated ability to approach difficult problems with enthusiasm and creativity and to effectively change focus when necessary.
• Advanced verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information to multi-disciplinary teams and non-cyber experts and advise senior management and/or external sponsors and proficient interpersonal skills.
• Highly advanced 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.
• Advanced experience creating technical direction and vision, writing research proposals, and/or securing sponsor funding.
• Significant experience in and knowledge of at least one of the following subject areas: network protocol analysis, cybersecurity data science, reverse engineering, and/or operational technology implementation.
• Highly advanced knowledge and experience in developing and applying advanced statistical/machine learning models and/or LLM tooling.