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Learning Operations Manager Jobs in Stockton, CA

Mathnasium

Math Learning Center Director

Manteca, CA · On-site

$24 - $30/hr

Manage and oversee all aspects of day-to-day operations in the center * Conduct sales by promptly ... Identify student needs and opportunities and develop customized student learning plans What we are ...

Sonoco

Operations- Emerging Leader Program

Oakdale, CA

$68K - $71K/yr

Operational Development -Technical training needed to excel in your role * Personal Development ... Leadership Development -Learning how to communicate vision, increase engagement, effectively manage ...

Mathnasium LLC.

Math Learning Center Director

Manteca, CA · On-site

$44K - $59K/yr

Manage and oversee all aspects of day-to-day operations in the center * Conduct sales by promptly ... Identify student needs and opportunities and develop customized student learning plans What we are ...

SONOCO CANADA

Operations- Internship

Oakdale, CA · On-site

$5.1K/mo

S locations, Sonoco's internship program will equip you with on-the-job learning experiences, plant ... management and other fields. In a Sonoco internship, you can expect: 12 week paid internship ...

Sonoco

Operations- Internship

Oakdale, CA

$5.1K/mo

S locations, Sonoco's internship program will equip you with on-the-job learning experiences, plant ... chain management and other fields. In a Sonoco internship, you can expect: * 12 week paid ...

Graham Packaging Company

Manager Production

Modesto, CA · On-site

$95K - $143K/yr

... learning, and taking action for continuous improvement and growth. Overview Production Managers ... Manages temporary staffing levels for the operation to achieve plant objectives for labor ...

Graham Packaging Company

Manager Production

Modesto, CA · On-site

$95K - $143K/yr

... learning, and taking action for continuous improvement and growth. Production Managers direct ... Manages temporary staffing levels for the operation to achieve plant objectives for labor ...

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All JobsLearning Operations JobsLearning Operations Manager JobsLearning Operations Manager Jobs in Stockton, CA

Learning Operations Manager information

See Stockton, CA salary details

$32.7K

$66.8K

$124.8K

How much do learning operations manager jobs pay per year?

As of Sep 12, 2026, the average yearly pay for learning operations manager in Stockton, CA is $66,841.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,200.00 and $81,600.00 per year, depending on experience, location, and employer.

What is a learning operations manager?

A Learning Operations Manager is responsible for overseeing the planning, execution, and optimization of training programs within an organization. They coordinate logistics, manage learning technologies, and ensure that educational initiatives run smoothly and efficiently. This role often works closely with instructional designers, trainers, and other stakeholders to align learning activities with organizational goals. Their work helps to maximize the impact and effectiveness of professional development and training efforts.

How does a learning operations manager typically collaborate with instructional designers and trainers within an organization?

A Learning Operations Manager works closely with instructional designers to ensure that course development aligns with organizational goals, timelines, and quality standards. They coordinate with trainers to schedule sessions, manage resources, and gather feedback for continuous improvement. Regular meetings and open communication channels are essential to address logistical challenges, troubleshoot issues, and ensure a seamless learning experience for participants. This collaborative approach helps streamline training delivery and promotes a culture of ongoing learning within the organization.

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

To thrive as a Learning Operations Manager, you need expertise in program management, data analysis, instructional design, and often a background in education or business. Familiarity with learning management systems (LMS), project management tools, and data reporting platforms is typically required. Strong organizational skills, problem-solving abilities, and effective communication set top performers apart in this role. These competencies ensure smooth delivery of training programs, data-driven improvements, and alignment with organizational learning goals.

What is the difference between Learning Operations Manager vs Learning Coordinator?

AspectLearning Operations ManagerLearning Coordinator
CredentialsTypically requires a bachelor’s degree in education, business, or related field; certifications in learning management systems (LMS) are commonUsually requires a bachelor’s degree; certifications in training or LMS are beneficial
Work EnvironmentOversees learning programs, manages teams, and collaborates with stakeholders in corporate or educational settingsSupports training sessions, coordinates schedules, and assists in content delivery within organizations
Employer & Industry UsageUsed in corporate training, e-learning companies, and educational institutionsCommon in corporate training departments, nonprofits, and educational organizations

The Learning Operations Manager focuses on managing learning programs, teams, and operational processes, while the Learning Coordinator handles logistical support and coordination of training activities. Both roles require knowledge of learning systems, but the manager has broader responsibilities in strategy and oversight.

What job categories do people searching Learning Operations Manager jobs in Stockton, CA look for?

The top searched job categories for Learning Operations Manager jobs in Stockton, CA are:

What cities near Stockton, CA are hiring for Learning Operations Manager jobs?

Cities near Stockton, CA with the most Learning Operations Manager job openings:

Learning Operations Manager jobs near you
Infographic showing various Learning Operations Manager job openings in Stockton, CA as of August 2026, with employment types broken down into 83% Full Time, 14% Part Time, 1% Temporary, and 2% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $66,841 per year, or $32.1 per hour.

Machine Learning - Postdoctoral Researcher

Livermore, CA • On-site

LLNL
Clean Energy Services • 5 - 10K employees
Learn more about LLNLexternal

$138K/yr

Full-time

Retirement

Re-posted 4 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're looking for a Machine Learning Postdoctoral Researcher to contribute to fundamental R&D in machine learning and statistical methods in support of different projects related to AI Safety & Security, Foundation Models in areas such as material science or bio assurance, and uncertainty quantification for deep learning models. These will be interdisciplinary projects that aim to combine state-of-the-art machine learning models with various science objectives. Examples are multi-modal sequence-to-sequence models for molecules and chemical reactions or combine large language models with other modalities. Furthermore, you will develop methods to improve safety and trustworthiness of these models. This position will be in the Machine Intelligence Group in the Center for Applied Scientific Computing (CASC) Division within the LLNL Computing Directorate.
You will
  • Research, design, implement, and apply advanced machine learning methods for multiple applications in a collaborative scientific environment.
  • Actively participate with project scientists and engineers in defining, planning, and formulating experimental, modeling, and simulation efforts for complex problems stemming from national security applications.
  • Propose and implement advanced analysis methodologies, collect and analyze data, and document results in technical reports and peer-reviewed publications.
  • Contribute to grant proposals and collaborate with others in a multidisciplinary team environment, including academic and industrial partners, to accomplish research goals.
  • Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internal and external to the Laboratory.
  • Perform other duties as assigned.

Qualifications
  • Must be eligible to access the Laboratory in compliance with Section 3112 of the National Defense Authorization Act (NDAA). See Additional Information section below for details.
  • Recent Ph.D. in Machine Learning, Optimization, Computer Science, Mathematics or a related field.
  • Demonstrated ability and desire to obtain substantial domain knowledge in fields of application to enable effective communication with subject matter experts, and to identify novel, impactful applications of machine learning.
  • Experience developing, implementing and applying advanced statistical or machine learning models and algorithms using modern software libraries such as PyTorch, TensorFlow, or similar as evidence through medium to large scale deep learning models and experiments.
  • Demonstrated research productivity, as documented by publications, reports, presentations, and/or open-source software in relevant venues (NeurIPS, ICML, ICLR, CVPR, AAAI, AISTATS, UAI, KDD, JMLR, Nature etc.)
  • Experience with scientific programming in the Python ecosystem as evidence through software artifacts, such as deep learning models, workflows, simulations, or similar
  • Experience with one or more of the following areas of deep learning: large language models, graph neural networks, multimodal models, generative models, robustness, explainable AI

Qualifications We Desire
  • Experience with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods including running numerical simulations of complex workflows
  • Demonstrated technical leadership in fields related to machine learning, such as mentorship or managing teams.
  • Experience or interest in scientific applications, such as, material science, climate science, etc.

Pay Range
$138,480 Annually
This is the lowest to highest salary range in good faith 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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