Physics-Informed Machine Learning Specialist

Reposted 21 Days Ago
Be an Early Applicant
Livermore, CA, USA
Hybrid
176K-267K Annually
Senior level
Information Technology • Security • Energy • Defense
The Role
The Physics-Informed Machine Learning Specialist will integrate AI/ML with physics-based applications, lead technical projects, and optimize algorithms for national security uses.
Summary Generated by Built In
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 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.

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.

These positions will be filled at either level based on knowledge and related experience as assessed by the hiring team. Additional job responsibilities (outlined below) will be assigned if hired at the higher level.

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

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.  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.

Skills Required

  • Master's degree in Engineering, Machine Learning, Statistics, Applied Mathematics, Computer Science or related field
  • Ability to secure and maintain a U.S. DOE Q-level security clearance
  • Advanced level knowledge and significant experience in AI, ML or data science
  • Significant experience directing, leading, developing, and executing independent research projects
  • Advanced organizational, verbal, and written communication skills

Lawrence Livermore National Laboratory Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Lawrence Livermore National Laboratory and has not been reviewed or approved by Lawrence Livermore National Laboratory.

  • Retirement Support A 401(k) with dollar-for-dollar match up to 6% plus additional employer contributions and immediate vesting strengthens total rewards. Clear plan tracks (TCP1/TCP2) and service-based contributions add predictability and long-term value.
  • Healthcare Strength Multiple medical, dental, and vision options, alongside FSAs and an Employee Assistance Program, provide comprehensive coverage. Ongoing open-enrollment updates and published plan details signal active plan management.
  • Leave & Time Off Breadth Paid time off includes vacation, sick leave, and up to 12 holidays, with a paid parental leave program for bonding. Flexibility is reinforced by leave advances and a catastrophic leave-sharing program for serious needs.

Lawrence Livermore National Laboratory Insights

Am I A Good Fit?
beta
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.

The Company
9,757 Employees
Year Founded: 1952

What We Do

Lawrence Livermore National Laboratory (LLNL) applies science and technology to make the world a safer place, focusing on national security missions such as nuclear deterrence, nonproliferation, energy security, defense, and intelligence.

Similar Jobs

PwC Logo PwC

Connected Supply Chain, Planning - Kinaxis, Manager

Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Hybrid
18 Locations
370000 Employees
99K-232K Annually

PwC Logo PwC

Strategy& Financial Services - AWM Consulting Manager

Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Hybrid
14 Locations
370000 Employees
99K-232K Annually

PwC Logo PwC

Connected Supply Chain, Planning - Kinaxis, Senior Associate

Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Hybrid
18 Locations
370000 Employees
77K-202K Annually

Cox Enterprises Logo Cox Enterprises

Communications Specialist

Artificial Intelligence • Automotive • Greentech • Information Technology • Machine Learning • Software • Cybersecurity
Remote or Hybrid
United States
50000 Employees
61K-92K Annually

Similar Companies Hiring

Milestone Systems Thumbnail
Artificial Intelligence • Security • Software • Analytics • Big Data Analytics
Lake Oswego, OR
1500 Employees
Golden Pet Brands Thumbnail
Digital Media • eCommerce • Information Technology • Marketing Tech • Pet • Retail • Social Media
El Segundo, California
178 Employees
Outpost Space Thumbnail
Aerospace • Defense
US
24 Employees

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account