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Machine Learning Engineer Jobs in Stockton, CA (NOW HIRING)

Talentry, LLC

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CNC Machinist - 5-axis

Livermore, CA · On-site

$27 - $45/hr

We take immense pride in the fact that all our machinery is fully designed, engineered, and ... A supportive, continuous-learning workspace that values your individual contributions. Important ...

Ichor Systems

Manufacturing Engineer

Livermore, CA · On-site

$81K - $138K/yr

Study production and machine requirements * Develop and test effective automated and manual systems ... Passion for learning and a drive to succeed Skills, Knowledge, and Abilities. * Analytical and ...

FM Industries

Engineer, Sustaining

Livermore, CA · On-site

$100K - $145K/yr

Health Spending Plans * Comprehensive Online Learning Center - houses thousands of training ... Knowledge of machining, assembly, welding, brazing, anodizing, cleaning, and other precision ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Stockton, CA

Machine Learning Engineer information

See Stockton, CA salary details

$33.2K

$135.6K

$203.8K

How much do machine learning engineer jobs pay per year?

As of Aug 9, 2026, the average yearly pay for machine learning engineer in Stockton, CA is $135,638.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,900.00 and $163,300.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Stockton, CA? The most popular types of Machine Learning Engineer jobs in Stockton, CA are:
What job categories do people searching Machine Learning Engineer jobs in Stockton, CA look for? The top searched job categories for Machine Learning Engineer jobs in Stockton, CA are:
What cities near Stockton, CA are hiring for Machine Learning Engineer jobs? Cities near Stockton, CA with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Stockton, CA as of August 2026, with employment types broken down into 77% Full Time, and 23% Contract. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $135,638 per year, or $65.2 per hour.

Atmospheric Sciences - Postdoctoral Researcher

LLNL

Livermore, CA • On-site

$123K/yr

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 an opening for an Atmospheric Science-Postdoctoral Researcher to work in the areas of clouds and precipitation with the goal of improving performance of global storm resolving models through evaluation and diagnosis using Department of Energy Atmospheric Radiation Measurement program observations. Research topics may include the mechanistic understanding of clouds, convection, precipitation and land-atmosphere interactions.
This is a two-year Postdoctoral appointment with the possibility of extension to a maximum of three years.
This position is in the Atmospheric, Earth, and Energy Division which is part of the Physical and Life Sciences Directorate.
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.
In this role, you will
  • Conduct research on the processes governing the transitions in boundary layer turbulence, clouds, convection, precipitation, and land-atmosphere interaction.
  • Diagnose and improve global storm resolving models using ground-based and satellite observations and machine learning.
  • Perform modeling tasks using cloud resolving models or large-eddy simulations.
  • Contribute to and actively participate in the conception, design, and execution of research to address defined problems.
  • Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internally and externally to the Laboratory.
  • Collaborate with others in a multidisciplinary team environment to accomplish research goals.
  • Publish research results in peer-reviewed scientific or technical journals and present results at external conferences seminars and/or technical meetings.
  • Travel as required to coordinate research with collaborators.
  • Perform other duties as assigned.

Qualifications
  • PhD in Atmospheric Sciences or a related field.
  • Experience and expertise in one or more of the following areas: cloud microphysics, turbulence and cloud schemes, convective-scale modeling, observational analysis, machine learning
  • Ability to perform as an innovative experimentalist with a broad range of experience in experimental design, techniques, and execution.
  • Experience developing independent research projects, including publication of peer-reviewed literature.
  • Proficient verbal and written communication skills to collaborate effectively in a team environment and present and explain technical information.
  • Effective initiative and interpersonal skills and ability to work in a collaborative, multidisciplinary team environment.

Qualifications we desire
  • Experience with deep learning and emulation
  • Experience with subgrid-scale parameterization development
  • Experience with C++ programing environment
  • Experience with land processes and earth system modeling

Pay Range
$123,048 Annually
This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. 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 Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date.
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
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 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
The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitlesjob 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 .

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