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Learning Engineer Jobs in California (NOW HIRING)

Capital One

Lead Machine Learning Engineer

San Francisco, CA · On-site +1

$120K - $159K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

San Jose, CA · On-site

$120K - $158K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Plenful

Machine Learning Engineer

San Francisco, CA · On-site

About the Role We're looking for a Machine Learning Engineer to design, build, and deploy production-grade ML systems that power the next generation of Plenful's AI platform. You'll own the end-to ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Capital One

Lead Machine Learning Engineer (IC)

San Jose, CA · On-site +1

$120K - $158K/yr

Lead Machine Learning Engineer (IC) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Gritt

Robot Learning Engineer

South San Francisco, CA · On-site

Robot Learning Engineer Location: SF Bay Area (in-person) About the role We're looking for an experienced Robot Learning Engineer to join our team. As an early member, you will play a pivotal role in ...

Qubeaxis

Machine Learning Engineer

San Francisco, CA · On-site

$130 - $180/hr

Job Title Machine Learning Engineer Job ID 20985 Location Work Mode Onsite About the Team Our ML Platform team builds intelligent systems that power recommendations, forecasting, ranking ...

Advatix Inc.

Machine Learning Engineer

San Mateo, CA · On-site

$110 - $165/hr

Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift: N/A Location: San Mateo, CA (Peninsula) - Onsite Preferred Schedule: Full time, Permanent Role Visa ...

Capital One

Sr. Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

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All JobsLearning Engineer JobsLearning Engineer Jobs in California

Learning Engineer information

See California salary details

$37.5K

$114.3K

$189K

How much do learning engineer jobs pay per year?

As of Aug 20, 2026, the average yearly pay for learning engineer in California is $114,347.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,900.00 and $149,500.00 per year, depending on experience, location, and employer.

What is a learning engineer?

A Learning Engineer is a professional who designs, develops, and implements educational experiences using principles from learning science, technology, and instructional design. They work to create effective learning environments, often integrating digital tools and data analytics to enhance teaching and learning outcomes. Learning Engineers collaborate with educators, subject matter experts, and technologists to build solutions that address specific educational challenges.

What are the key skills and qualifications needed to thrive as a learning engineer?

To thrive as a Learning Engineer, you need expertise in instructional design, learning science, and educational technology, often supported by a degree in education, instructional design, or a related field. Familiarity with learning management systems (LMS), authoring tools like Articulate or Adobe Captivate, and data analytics platforms is typically required. Strong collaboration, problem-solving, and communication skills distinguish top performers in this role. These competencies are crucial for designing effective, scalable learning experiences that meet diverse learner needs and organizational goals.

How do learning engineers typically collaborate with subject matter experts and instructional designers during course development?

Learning Engineers play a pivotal role in bridging technical solutions and educational goals. They often work closely with subject matter experts to deeply understand the content, ensuring its accurate representation in digital formats. Collaboration with instructional designers is essential, as Learning Engineers translate pedagogical strategies into interactive and accessible learning experiences, utilizing technologies such as learning management systems, analytics, and multimedia tools. Effective communication and iterative feedback are key, as these teams work together to design, test, and refine educational products that maximize learner engagement and success.

What is the difference between Learning Engineer vs Instructional Designer?

AspectLearning EngineerInstructional Designer
Required CredentialsBachelor's or master's in education, instructional design, or related fields; familiarity with e-learning toolsBachelor's or master's in education, instructional design, or related fields; expertise in curriculum development
Work EnvironmentCollaborates with developers, data analysts, and educators to build digital learning solutionsDesigns and develops educational content and curricula for various learning settings
Employer & Industry UsageTech companies, online education platforms, corporate trainingSchools, universities, corporate training departments

Learning Engineers focus on developing and implementing innovative digital learning solutions using technology and data analysis, while Instructional Designers primarily create educational content and curricula. Both roles require similar educational backgrounds and often work in overlapping industries, but their core responsibilities differ in approach and focus.

Are machine learning engineers still in demand?

Machine learning engineers remain in high demand due to the growing adoption of AI and data-driven solutions across industries. They typically require skills in programming, data analysis, and familiarity with tools like TensorFlow or PyTorch, and often hold advanced degrees in related fields. The role is expected to continue growing as organizations prioritize automation and intelligent systems.

What does a learning engineer do?

A learning engineer designs, develops, and implements educational programs and digital learning solutions. They analyze learning needs, create instructional content, and often use tools like learning management systems (LMS) to enhance training effectiveness. Strong skills in instructional design, technology, and data analysis are essential for this role.

What are popular job titles related to Learning Engineer jobs in California?

For Learning Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Learning Engineer jobs in California look for?

The top searched job categories for Learning Engineer jobs in California are:

Learning Engineer jobs near you
Infographic showing various Learning Engineer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $114,347 per year, or $55 per hour.

Machine Learning Engineer, Reinforcement Learning

Skild AI

San Mateo, CA

Full-time

Re-posted 11 days ago

Job description

Position Overview

We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and optimizing these models to perform efficiently in real-world robotic environments. This will require close collaboration with our robotics, research, and engineering team. Your work will directly impact the development of intelligent, adaptable robots capable of learning and performing complex tasks autonomously.

Responsibilities
  • Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.
  • Design and conduct experiments to train RL models and conduct real-world tests.
  • Collaborate closely with researchers to explore novel methods of scaling up reinforcement learning model training.
  • Communicate effectively with inference, application, and deployment engineers to integrate RL models into robotic systems and iterate on methods to enable robust deployment.
  • Analyze and interpret experimental results, iterating on model design to achieve desired performance.
  • Stay up-to-date with the latest research and advancements in reinforcement learning.
Preferred Qualifications
  • BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
  • Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
  • Deep understanding and practical experience with various reinforcement learning algorithms and techniques (model-free, model-based, multi-task, hierarchical, multi-agent, etc.).
  • Strong background in algorithms, data structures, and software engineering principles.
  • Experience with physics simulation engines and tools for training RL.
  • Deep understanding of state-of-the-art machine learning techniques and models.
  • Extensive industry experience with reinforcement learning and robotic systems.

Apply