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Learning Engineer Jobs in Arizona (NOW HIRING)

Machine Learning Engineer

Phoenix, AZ

$55.25 - $73.25/hr

Machine Learning Engineer Location: Phoenix, AZ (Onsite) Required Skills Machine Learning, Python, SQL, APIs, NLP, NoSQL, Spark / PySpark, CI/CD We are looking for a strong Machine Learning Engineer ...

Machine Learning Engineer Turn machine learning into real-world mission capability. PSG is seeking a Machine Learning Engineer to design, build, and deploy AI/ML solutions that power mission-critical ...

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As an Applied Machine Learning Engineer, you will support informed decision-making around the application of machine learning and AI models in safety- and reliability-constrained systems. This role ...

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the ...

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III you will be a team lead on the Marketplace Efficiency - Job Reach team. Your team will be responsible for maintaining ...

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Learning Engineer information

See Arizona salary details

$35.4K

$108K

$178.5K

How much do learning engineer jobs pay per year?

As of May 28, 2026, the average yearly pay for learning engineer in Arizona is $107,973.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,300.00 and $141,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Learning Engineer, and why are they important?

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 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 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.

What cities in Arizona are hiring for Learning Engineer jobs? Cities in Arizona with the most Learning Engineer job openings:
Infographic showing various Learning Engineer job openings in Arizona as of May 2026, with employment types broken down into 1% As Needed, 54% Full Time, 41% Part Time, 1% Temporary, and 3% Contract. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $107,973 per year, or $51.9 per hour.

$55.25 - $73.25/hr

Other

Posted 5 days ago


Job description

Machine Learning Engineer

Location: Phoenix, AZ (Onsite)

Required Skills

Machine Learning, Python, SQL, APIs, NLP, NoSQL, Spark / PySpark, CI/CD

Job Description

We are looking for a strong Machine Learning Engineer with hands-on experience in developing, deploying, and optimizing ML models in enterprise environments. The ideal candidate should have expertise in Classical Machine Learning, NLP, Python development, and scalable data processing systems.

Required Qualifications

Bachelor s or higher degree in Data Science, Computer Science, Engineering, Information Systems, or related field

Hands-on experience building and deploying Machine Learning models including Classical ML and NLP solutions

Strong understanding of ML algorithms, frameworks, libraries, and software architecture

Advanced Python programming experience; Java knowledge is a plus

Experience integrating ML models into existing applications in both batch and real-time environments

Strong SQL skills with experience writing complex queries and optimizing data pipelines

Experience with NoSQL databases is a plus

Familiarity with Big Data technologies such as Spark, PySpark, Hive, MapReduce

Working knowledge of UNIX/Linux commands

Experience using GitHub and CI/CD pipelines

Strong analytical, problem-solving, and communication skills

Experience with AI/ML governance in regulated industries is a plus

Preferred Experience

NLP model development

Enterprise-scale ML deployments

Real-time inference/API integrations

Financial services or highly regulated industry background