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Machine Learning Specialist Jobs in California (NOW HIRING)

... specialist, and optics improvement specialist Preferred Qualifications Experience with deep ... machine learning and/or computer vision techniques to build models integrated into industrial ...

This role sits within a multidisciplinary risk team of machine learning engineers, data scientists, risk strategy specialists, analytics engineers, product managers, and operations teams. You will ...

This role sits within a multidisciplinary risk team of machine learning engineers, data scientists, risk strategy specialists, analytics engineers, product managers, and operations teams. You will ...

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Machine Learning Specialist information

See California salary details

$20.2K

$53.2K

$95.7K

How much do machine learning specialist jobs pay per year?

As of Jul 30, 2026, the average yearly pay for machine learning specialist in California is $53,219.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,500.00 and $59,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Machine Learning Specialist position, and why are they important?

To thrive as a Machine Learning Specialist, you need a strong background in mathematics, programming (Python, R), and data analysis, typically supported by a relevant degree in computer science or a related field. Experience with machine learning frameworks such as TensorFlow, PyTorch, and knowledge of cloud platforms like AWS or Azure is highly valued, and certifications in these can enhance your qualifications. Strong problem-solving skills, curiosity, and the ability to communicate complex concepts clearly make someone stand out in this field. These skills and qualifications are crucial for effectively developing, deploying, and explaining machine learning solutions to diverse stakeholders.

What is a Machine Learning Specialist job?

A Machine Learning Specialist is a professional who designs, develops, and implements machine learning models and algorithms to solve complex problems. They work with large datasets, use statistical and computational techniques, and optimize models for accuracy and efficiency. Their role often involves data preprocessing, feature engineering, model selection, and deployment. They collaborate with data scientists, software engineers, and domain experts to integrate machine learning solutions into business applications.

What is a machine learning specialist?

A machine learning specialist is a professional who designs, develops, and implements algorithms that enable computers to learn from data and improve their performance over time. They often work with programming languages like Python or R, utilize machine learning frameworks such as TensorFlow or scikit-learn, and have strong skills in statistics and data analysis. This role typically requires a background in computer science, mathematics, or related fields, and may involve tasks like model training, evaluation, and deployment in various applications.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer or AI research director, often requiring advanced skills in deep learning, data analysis, and programming with tools like Python and TensorFlow. These roles usually involve leadership, strategic planning, and significant experience in the field, and they may be found in large tech companies or specialized AI firms.

What are some common challenges a Machine Learning Specialist might face in this role?

Machine Learning Specialists often encounter challenges such as ensuring data quality, selecting appropriate algorithms, and scaling solutions for real-world application. Navigating the complexities of messy or incomplete datasets and tuning models for optimal performance can be demanding. Balancing innovation with practical deployment constraints, such as computational resources and integration with existing systems, is also common. To address these challenges, collaboration with data engineers, domain experts, and product teams is essential, and ongoing professional development helps specialists stay ahead in this rapidly evolving field.

What engineer makes $500,000 a year?

Senior machine learning specialists or AI engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or at leading tech companies can earn salaries around $500,000 annually. Such roles typically require advanced degrees, specialized certifications, and a strong track record of successful projects.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding complex algorithms, data preprocessing, and model optimization. While AI automation tools can assist with certain tasks, MLEs are essential for creating, maintaining, and improving AI systems, making complete replacement unlikely in the near term.
What are popular job titles related to Machine Learning Specialist jobs in California? For Machine Learning Specialist jobs in California, the most frequently searched job titles are:
Infographic showing various Machine Learning Specialist job openings in California as of July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $53,219 per year, or $25.6 per hour.

Physics-Informed Machine Learning Specialist

LLNL

Livermore, CA • On-site

Full-time

Retirement

Re-posted 26 days ago


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

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.