Physics-Informed Machine Learning Specialist

Physics-Informed Machine Learning Specialist Mid-Senior Level | Full-time Engineering | Livermore, CA | 05/05/2026 Reference #: REF8321H Job Code: SES.3 Science & Engineering MTS 3 / SES.4 Science & Engineering MTS 4 Organization: Engineering Position Type: Career Indefinite Security Clearance: Anticipated DOE Q clearance (requires U.S. citizenship and a federal background investigation) Drug Test: Required for external applicant(s) selected for this position (includes testing for use of marijuana) Medical Exam: Not applicable Apply Now Job Description We have multiple openings for a Physics-Informed Machine Learning Specialist with a strong technical background in integrating artificial intelligence (AI) and machine learning (ML) methodologies with physics-based applications in engineering. You will combine existing AI/ML methodologies with state-of-the-art computational modeling and simulation capabilities on high-performance computing (HPC) architectures to develop novel application areas within Lawrence Livermore National Laboratory’s (LLNL) national security mission space. You will contribute to research and development in advanced simulation capabilities related to optimizing algorithms and models, surrogate model development, model validation, reliability, uncertainty quantification, and data engineering. You will work closely with other groups to support the missions of the Laboratory. You will work closely with multidisciplinary teams and programmatic customers to ensure application needs are met. These positions are in the Computational Engineering Division (CED), within the Engineering Directorate. In this role you will Provide technical leadership and guidance to project teams developing state-of-the-art methods and applying research results to meet programmatic goals, while balancing priorities of customers and partners to ensure deadlines are met. Solve abstract and complex problems as required, using in-depth analysis, and drawing from advanced level technical knowledge, best practices, and both routine and innovative techniques and approaches. Serve as the primary technical point of contact for program managers internally and at sponsor and partner organizations by sharing relevant advanced level knowledge and providing opinions and recommendations on methodologies, as needed to fulfill deliverables and best meet sponsor needs. Utilize advanced level knowledge and skills and apply significant experience in one or more of the following areas of computational science and engineering to new areas at the intersection of artificial intelligence and national security: computational mechanics, chemistry, physics, or materials, nuclear engineering, electrical engineering, non-destructive evaluation, robotics and control, optical systems, high performance computing, or other relevant area of computational science and engineering. Develop and apply complex algorithms in one or more of the following machine learning areas/tasks to areas of national security: deep learning, unsupervised/self-supervised learning, representation learning, zero- or few-shot learning, active learning, reinforcement learning, natural language processing, ensemble methods, statistical modeling and inference, performance optimization (scalability, novel hardware, etc.), physics informed machine learning, agentic AI workflows. Perform other duties as assigned. Additional job responsibilities at the SES.4 level Establish and implement broad project vision and strategy and influence technical direction and decisions for self and others to drive successful project outcomes. Develop novel and innovative Engineering research, technologies, capabilities, and methodologies enabled by the use or integration of applied statistics, machine learning and artificial intelligence, and/or uncertainty quantification. Provide subject matter expertise and conduct highly complex and in-depth analysis within one or more areas of machine learning and artificial intelligence, applied statistics, and/or uncertainty quantification. Qualifications Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship. Master’s degree in Engineering, Machine Learning, Statistics, Applied Mathematics, Computer Science or related technical field or the equivalent combination of education and related experience. Advanced level knowledge and significant experience in artificial intelligence, machine learning or data science, and developing applications in one or more of the following areas: mechanical engineering, aerospace engineering, computational mechanics, electrical engineering, applied statistics, uncertainty quantification, or a related technical area. Significant experience directing, leading, developing, and executing independent research projects. Advanced organizational, verbal and written communication, and interpersonal skills to collaborate effectively in a multidisciplinary team environment, and with subject matter experts, including authoring reports, presenting, and explaining complex technical information. Significant experience working effectively in a team environment with multi-disciplinary personnel while managing multiple concurrent tasks and deliverables. Additional qualifications at the SES.4 level Subject matter expertise of highly advanced concepts in machine learning or data science and significant experience developing applications in one or more of the following areas: physics, mechanical engineering, aerospace engineering, computational mechanics, electrical engineering, applied statistics, uncertainty quantification, or a related technical area. Significant experience and demonstrated ability to successfully lead technical personnel and projects and perform project planning and execution, including applying and developing creative and innovative solutions to highly complex problems. Expert communication, facilitation, interpersonal, and collaboration skills necessary to effectively lead a team, present and explain information and influence and advise senior management and stakeholders, while positively representing the Program and the Laboratory. Qualifications We Desire Ability to obtain and maintain Sensitive Compartmented Information (SCI) access which requires U.S. citizenship. PhD in Engineering, Machine Learning, Statistics, Applied Mathematics, Computer Science, or a related technical field, or the equivalent combination of education and related experience. Significant experience developing, deploying, and/or utilizing multi-physics simulation codes for massively parallel, high-performance computing architectures utilized by DOE and DoD stakeholders. 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

Position Information This is a Career Indefinite position, open to Lab employees and external candidates. Equal Opportunity Employer 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. #J-18808-Ljbffr Lawrence Livermore National Laboratory