Machine Learning Researcher

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 Machine Learning and Data Analysis expert to join our team and advance the discipline as well as apply cutting edge tools and techniques to some of society's most important problems. You will work with and lead multi-disciplinary teams consisting of machine learning experts, data science practitioners, analysis experts, and domain scientists in areas ranging from fundamental research in machine learning, development, deployment, and performance optimization of large scale AI models, to applied AI and analysis problems in fields such as high energy density physics, material science, predictive medicine, and treatment discovery. You will also have the opportunity develop research strategies in these areas and engage with a variety of related research projects in parallel computing, data analysis and visualization, or applied mathematics. This position is in the Center for Applied Scientific Computing (CASC) Division within the Computing Directorate. Essential Duties Establish independent research thrusts through strategic engagements with internal and external sponsors. Lead mid- to large-sized research teams in applied machine learning and data analysis in support of one or more mission related scientific applications. Provide strategic guidance to LLNL management and demonstrate technical leadership in the research community. Research, develop, implement, and evaluate new machine learning and data analysis techniques for multiple applications in a collaborative scientific environment. Actively participate with project scientists and engineers in defining, planning, and formulating experimental, modeling, and simulation efforts for complex problems stemming from national security applications. Provide guidance to subject matter experts in various fields to jointly explore the potential for machine learning research to solve domain specific challenges. Adapt current machine learning research to real world applications at scale, with potentially limited and noisy data, with a high consequence of error, and guide the development of practical solutions. Present and disseminate research results at scientific conferences and in peer-reviewed publications. Establish future research directions and author grant proposals including presentations to programmatic sponsors and external funding agencies. Collaborate with a broad spectrum of scientists and engineers, internally and externally, to accomplish research goals. Perform other duties as assigned. In Addition, At SES.5 Level Provide scientific and technical direction for large projects and programs. Support lab leadership in attracting retaining projects, programs, funding, and staff. Engage and influence senior management, policy makers, and external sponsors. Qualifications Ph.D. in Computer Science, Applied Mathematics, Statistics or related field or the equivalent combination of education and related experience. 8+ years of experience post PhD in research in machine learning and data analysis Significant experience in foundational or applied machine learning research area and large scale data analysis. Experience independently developing, implementing, and applying advanced statistical tools, machine learning models, and data analysis algorithms using modern software libraries such as C++, PyTorch, TensorFlow, or similar as evidence through medium to large scale models, applications, and experiments. Demonstrated research productivity, as documented by publications, reports, presentations, and/or open-source software in high impact venues, such as, IEEE Transactions, NeurIPS, ICML, MLST, PNAS, etc. Significant experience in working with diverse teams to solve complex problems and deliver practical solutions. Substantial record of sustained program development and strategic engagement in fields related to machine learning and data analysis. Experience leading research teams in achieving long term objectives and delivering solutions. Expert verbal and written communication and interpersonal skills necessary to effectively collaborate with internal and external teams to present and explain technical information and to advise senior management and external sponsors. Experience in working with subject matter experts in one or more areas, such as physics, biology, or engineering. In Addition, at the SES.5 Level Record of sustained engagement with regulators, funding agencies, top level management, or other oversight agencies. Demonstrated record of program development in machine learning, data analysis, or related fields. Experience providing scientific and technical directions to R&D teams delivering innovative approaches with significant impact and internal and external recognition. Desired Qualifications Experience with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods including running numerical simulations or complex workflows Pay Range

• 210,630 - $320,580 Annually
• 210,630 - $267,060 Annually for the SES.4
• 252,810 - $320,580 Annually for the SES.5

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 All your information will be kept confidential according to EEO guidelines. 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 Security Clearance None required. However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process. This process includes completing an online background investigation form and receiving approval of the background check. National Defense Authorization Act (NDAA) The 2025 National Defense Authorization Act (NDAA), Section 3112, generally prohibits citizens of China, Russia, Iran and North Korea without dual US citizenship or legal permanent residence from accessing specific non-public areas of national security or nuclear weapons facilities. The restrictions of NDAA Section 3112 apply to this position. To be qualified for this position, Candidates must be eligible to access the Laboratory in compliance with Section 3112. 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: 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. LLNL