Research Scientist - Computer Vision and Machine Learning

Research Scientist

• Computer Vision and Machine Learning Lawrence Livermore National Laboratory tuition reimbursement, 401(k), relocation assistance, remote work United States, California, Livermore May 14, 2026 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. Job Description We have an opening for a Research Scientist in Computer Vision and Machine Learning to develop advanced algorithms and software for image and video understanding in support of problems of national importance. This role sits at the intersection of computer vision, image processing, software engineering and applied machine learning. You will work in a collaborative, multidisciplinary environment alongside experts in computer vision, machine learning, scientific computing, and domain science. This role combines fundamental research with the development of robust, reproducible software systems that support mission-critical applications. This position is in the Computational Engineering Division (CED), within the Engineering Directorate. 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. This position will be filled at eitherlevel based on knowledge and related experience as assessed by the responsibilities (outlined below) will be assigned if hired at the higher level. You will Conduct original research in computer vision, image processing, and machine learning. Develop, test, and evaluate algorithms for tasks such as segmentation, tracking, temporal reasoning, scene understanding, anomaly detection, multimodal fusion, and perception under uncertainty or occlusion. Build models and software that perform robustly on noisy and sparse data. Design and execute rigorous experiments, benchmarking strategies, and error analyses to assess model performance, reliability, and limitations. Develop research software using disciplined engineering practices, including code review, testing, documentation, version control, and traceability. Establish and maintain reproducible MLOpsworkflows for data preparation, experiment tracking, model and dataset versioning, automated training and evaluation, packaging, and deployment. Present results at reviews, seminars, and scientific meetings, and publish in peer-reviewed venues as appropriate. Perform other duties as needed. Additional job responsibilities, at the SES.3 level Provide technical leadership and guidance to multiple diverse, technical teams of LLNL scientists and engineers to operationalize research and development advancements for LLNL national security programs, while executing projects and tasks and balancing priorities of customers and partners to ensure deadlines are met. Independently determine technical objectives and criteria to satisfy project deliverables and execute the appropriate technical approaches. Oversee the activities of other personnel, providing informal mentoring and guidance to less-experienced team members. Qualifications Ability to secureand maintain a

U.S. DOE

Q-level security clearance which requires U.S. citizenship. Master's degree in computer science, data science, applied mathematics, or a related field with emphasis in machine learning, image processing, or scientific computing, or the equivalent combination of education and related experience . Comprehensive knowledge and experience in computer vision and machine learning, especially for image or video data. Experience with Python programming skills and comprehensive experience in applied machine learning, including developing and evaluating models using PyTorch or TensorFlow. Demonstrated experience with reproducible ML workflows, experiment tracking, model and dataset versioning, automated evaluation and testing. Experience with AI coding agents to support agentic development, accelerate research iteration, automate experimentation, and enable reproducible software development. Proficient verbal and written communication skills necessary to effectively collaborate in a multi-disciplinary team. Demonstrated analytical, problem-solving, and decision-making skills to effectively develop creative solutions to moderately complex problems. Ability to travel off-site for sponsor and customer interactions. Additional qualifications at the SES.3 level PhD in computer science, data science, applied mathematics, or a related field with emphasis in computer vision, machine learning, image processing, or the equivalent combination of education and related experience. Advanced level knowledge in one or more of the following areas: computer vision, video object segmentation, multi-object tracking. Advanced leadership skills and experience and demonstrated ability to exercise independent judgment to effectively manage diverse technical teams in executing projects. Ability to independently develop and execute complex analyses and to prepare and finalize tailored reports. Advanced verbal and written communication skills necessary to effectively collaborate in a multidisciplinary team and present technical information to a variety of audiences. Qualifications We Desire Experience in one or more of the following: video understanding, multi-object tracking, segmentation, scientific imaging, remote sensing, sensor fusion, multimodal learning, or autonomous perception. Experience deploying or sustaining computer vision or ML systems in operational or mission-critical environments.

Experience working with high-performance computing, distributed training, or large-scale data processing environments. Experience maintaining or modernizing codes while preserving reliability and continuity of operations. Familiarity with secure, regulated, or high-consequence research and engineering environments. Ability to balance exploratory research with delivery, documentation, validation, and stakeholder needs. Pay Range $146,340

• $222,564 Annually $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; 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 2026Best Places to Work by Glassdoor! FlexibleBenefits Package 401(k) Relocation Assistance Education Reimbursement Program Flexible schedules (

• depending on project needs) Our values
• visithttps://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 willinitiate a Federal background investigation to determine if youmeet 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 useand/or possession ofmobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area whereyou are not permitted to have a personal and/or laboratory mobile devicein your possession. This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices. Ifyou useamedical device, whichpairs with a mobile device,you must still follow the rules concerningthe mobile device in individual sections within Limited Areas. Sensitive Compartmented Information Facilities requireseparate 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. CaliforniaPrivacy Notice The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitlesjob 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.