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Artificial Intelligence Machine Learning Physics Jobs

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How much do artificial intelligence machine learning physics jobs pay per hour?

As of Jun 5, 2026, the average hourly pay for artificial intelligence machine learning physics in the United States is $20.06, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $25.48 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Artificial Intelligence Machine Learning Physicist, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Physicist, you need a strong background in physics, advanced mathematics, computer science, and experience with machine learning algorithms, typically supported by a graduate degree in a related field. Proficiency in programming languages such as Python or C++, machine learning frameworks like TensorFlow or PyTorch, and familiarity with data analysis tools are essential, along with experience in scientific computing. Critical thinking, problem-solving, and strong communication skills help you interpret complex data, collaborate across disciplines, and convey research findings effectively. These combined skills are crucial for developing innovative AI models, driving scientific discovery, and advancing technology at the intersection of physics and machine learning.

What collaborative projects can professionals in Artificial Intelligence Machine Learning Physics expect to work on?

Professionals in Artificial Intelligence Machine Learning Physics often work on interdisciplinary teams, partnering closely with data scientists, physicists, and software engineers. They may contribute to projects such as developing advanced simulation tools, optimizing experimental data analysis, or creating machine learning models to predict physical phenomena. Collaboration is key, as these roles frequently involve integrating AI algorithms with physical models and leveraging domain-specific knowledge from physics experts. This dynamic environment fosters continual learning and offers opportunities to lead innovative research or transition into specialized engineering and research leadership roles.

What is Artificial Intelligence Machine Learning Physics?

Artificial Intelligence Machine Learning Physics is an interdisciplinary field that applies AI and machine learning techniques to solve complex problems in physics. Experts in this area use algorithms to analyze large datasets, model physical phenomena, and accelerate scientific discoveries. The field combines knowledge of physics, computer science, and mathematics to design models that can predict, simulate, or interpret physical processes. Applications include materials science, quantum mechanics, astrophysics, and more, making it a rapidly growing area of research and industry.

What is the difference between Artificial Intelligence Machine Learning Physics vs Data Scientist?

AspectArtificial Intelligence Machine Learning PhysicsData Scientist
Required credentialsDegree in Computer Science, Physics, or related fields; certifications in AI/MLDegree in Statistics, Mathematics, Computer Science; certifications in data analysis
Work environmentResearch labs, tech companies, academia focusing on AI/ML applications in physicsBusiness, finance, healthcare sectors analyzing large datasets
Industry usageDeveloping AI models for physics simulations, research, and technologyExtracting insights from data to inform business decisions

Artificial Intelligence Machine Learning Physics and Data Scientist roles share a focus on data analysis and technical skills. However, AI/ML Physics emphasizes developing algorithms within physics contexts, while Data Scientists focus on analyzing diverse datasets across industries. Both roles often require similar educational backgrounds and certifications, but their applications and work environments differ significantly.

More about Artificial Intelligence Machine Learning Physics jobs
What cities are hiring for Artificial Intelligence Machine Learning Physics jobs? Cities with the most Artificial Intelligence Machine Learning Physics job openings:
What states have the most Artificial Intelligence Machine Learning Physics jobs? States with the most job openings for Artificial Intelligence Machine Learning Physics jobs include:
Physics-Informed Machine Learning Specialist

Physics-Informed Machine Learning Specialist

LLNL

Livermore, CA โ€ข On-site

Full-time

Retirement

Posted yesterday


Job description

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
Wehave 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 eitherlevel 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 2026Best 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, wewill initiate 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
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