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Machine Learning Engineer Opt Jobs in Stockton, CA

This role requires aerospace or machining manufacturing experience and is responsible for CAD ... Passion for learning and a drive to succeed. Skills, Knowledge, and Abilities. * Analytical and ...

Manufacturing Engineer

Livermore, CA ยท 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 ...

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 ...

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CNC Machinist - 5-axis

Livermore, CA ยท 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 ...

New

Manufacturing Engineer 3 - NPI

Livermore, CA ยท On-site

$130K - $150K/yr

Health Spending Plans * Comprehensive Online Learning Center - houses thousands of training ... Knowledge of complex machining processes and equipment (mill, lathe, screw machine, etc.). * In ...

Showing results 41-60

Machine Learning Engineer Opt information

See Stockton, CA salary details

$33.2K

$135.6K

$203.8K

How much do machine learning engineer opt jobs pay per year?

As of Aug 7, 2026, the average yearly pay for machine learning engineer opt 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 into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges machine learning engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.
What are popular job titles related to Machine Learning Engineer Opt jobs in Stockton, CA? For Machine Learning Engineer Opt jobs in Stockton, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Opt jobs in Stockton, CA look for? The top searched job categories for Machine Learning Engineer Opt jobs in Stockton, CA are:
What cities near Stockton, CA are hiring for Machine Learning Engineer Opt jobs? Cities near Stockton, CA with the most Machine Learning Engineer Opt job openings:
Infographic showing various Machine Learning Engineer Opt job openings in Stockton, CA as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $135,638 per year, or $65.2 per hour.

Atmospheric Sciences - Postdoctoral Researcher

LLNL

Livermore, CA โ€ข On-site

$123K/yr

Full-time

Retirement

Re-posted 23 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 .