Machine Learning Research Engineer

About the role

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. We empower teams to tackle the toughest challenges of today and tomorrow.

Responsibilities

• Research, develop, implement, and evaluate new machine learning techniques for multiple applications in a collaborative scientific environment.
• Adapt and deploy common machine learning software stack on large-scale high performance computing clusters.
• 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.
• 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.
• Collaborate with a broad spectrum of scientists and engineers, internally and externally, to accomplish research goals.

Requirements

• M.S. in Computer Science, Applied Mathematics, Statistics or related field or the equivalent combination of education and related experience.
• Experience in at least one machine learning research area, such as, foundation models, representation learning, safety & robustness, uncertainty quantification, interpretability, physics-constrained ML, or graph-based learning as demonstrated in software artifacts or publications at high impact AI/AL focused venues.
• Experience developing, implementing, and applying advanced statistical or machine learning models and algorithms using modern software libraries such as PyTorch, TensorFlow, or similar as evidence through medium to large scale deep learning models and experiments.
• Experience in working with diverse teams to solve complex problems and deliver practical solutions.
• Comprehensive analytical and problem-solving skills necessary to craft creative solutions and solve complex problems.

Qualifications

• In addition to the requirements above, at the SES.3 Level:
• Ph.D. in Computer Science, Applied Mathematics, Statistics or related field or the equivalent combination of education and related experience.
• Demonstrated research productivity, as documented by publications, reports, presentations, and/or open-source software in high impact AI/ML focused venues, such as, NeurIPS, ICML, ICLR, CVPR, AAAI, AISTATS, UAI, KDD, or JMLR.
• Advanced verbal and written communication skills necessary to interact with a multi-disciplinary research team, author technical and scientific reports and papers, and deliver scientific presentations.

Desired Qualifications

• Experience with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods including running numerical simulations or complex workflows.
• Experience in working with subject matter experts in one or more areas, such as physics, biology, or engineering.
• Background in statistics, applied mathematics, or related area.

Pay Range

$146,340 - $222,564 Annually
$146,340 - $185,544 Annually for the SES.2 job level
$175,530 - $222,564 Annually for the SES.3 job level

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 https://www.llnl.gov/inclusion/our-values

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 includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

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.

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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.