Data Science Engineer

We have multiple openings for early-career Data Science Engineers to join a team applying machine learning, AI/NLP, and data science to national security challenges.

You will contribute to the design, development, and deployment of AI-driven capabilities — including large language models (LLM)-based pipelines, knowledge graphs, and intelligent agent prototypes — that advance data and decision sciences for national security.

Working alongside senior engineers and domain experts, you will write production-quality code, help build analytical tools and visualizations, and contribute fresh ideas to challenging problems.

These positions are in the Computational Engineering Division (CED), within the Engineering Directorate, in support of impactful Global Security Directorate missions.

Depending on your assignment, this position may offer a hybrid schedule, blending in-person and virtual presence.

You may have the flexibility to work from home one or more days per week.

You will Under the guidance of senior team members, apply machine learning and data science algorithms to help analyze national security datasets.

Contribute to LLM-driven data pipelines for information extraction, entity resolution, and automated analysis of large-scale structured and unstructured datasets.

Help build and maintain knowledge graphs and graph-based analytics (e.g., graph-RAG) to model relationships across national security domains.

Assist in prototyping AI agents and conversational interfaces that allow analysts to query data science capabilities through natural language.

Write clean, well-documented code to implement data science solutions, create visualizations, and support analytical tools, following software engineering best practices for version control, testing, and documentation.

Collaborate with multidisciplinary teams including intelligence analysts, domain scientists, and computer scientists in building research prototypes and capabilities.

Contribute to technical reports, internal presentations, and peer-reviewed publications and conference papers.

Perform other duties as assigned.

Ability to secure and maintain a U.S.

DOE Q-level security clearance, which requires U.S. citizenship.

Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, Physics, or a related technical field.

with Python programming and software development, including version control (Git), testing, and documentation (through academics, internships, or research projects).

Demonstrated experience developing generative AI solutions, such as building applications with LLMs, implementing retrieval-augmented generation (RAG), fine-tuning foundation models, or engineering LLM-driven data pipelines.

in the space domain, such as space domain awareness, satellite operations, orbital analysis, or applying data science methods to space-related datasets.

Sufficient communication and interpersonal skills necessary to collaborate in a multidisciplinary team environment and present technical information to varied audiences.

We Desire Master’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related technical field.

building LLM-driven workflows for automating question-answering, summarization, or structured report generation.

constructing knowledge graphs from extracted entities and relationships and applying graph-based retrieval (e.g., graph-RAG) to enable intelligent querying over complex domains.

developing AI agents or chatbot interfaces — using frameworks such as LangChain, LlamaIndex, or similar — that allow end users to interact with underlying data and models through natural language. Track record of publications, conference presentations, and deployed prototypes. Pay Range $121,830 - $154,500 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; 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. Additional Information: #LI-Hybrid 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 .