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Learning Engineer Jobs in Arizona (NOW HIRING)

S., Ascend Learning was recognized by Newsweek and Plant-A Insights Group as one of America's 2025 ... WHAT YOU'LL DO As a Principal AI Engineer, you will be pivotal in driving the evolution of our AI ...

AI Solutions Architect

Tempe, AZ ยท On-site

$60.25 - $79.50/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

Senior AI Engineer - SFL Scientific

Tempe, AZ ยท On-site

$100K - $137K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Civil Engineer

Phoenix, AZ ยท On-site

$45 - $60/hr

We hire and support both Civil Engineering and IT professionals, including Mobile Developers and Machine Learning Engineers, and partner with municipalities, transportation authorities, utilities ...

Civil Engineer

Phoenix, AZ ยท Hybrid

$45 - $60/hr

We hire and support both Civil Engineering and IT professionals, including Mobile Developers and Machine Learning Engineers, and partner with municipalities, transportation authorities, utilities ...

AI/ML Engineer II

Phoenix, AZ ยท On-site +1

$113K - $136K/yr

Work with cross-functional team to contribute to machine learning projects throughout the machine learning lifecycle to include analysis, solution design, data pipeline engineering, testing ...

AI/ML Engineer II

Phoenix, AZ ยท On-site

$116K - $139K/yr

Work with cross-functional team to contribute to machine learning projects throughout the machine learning lifecycle to include analysis, solution design, data pipeline engineering, testing ...

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Showing results 1-20

Learning Engineer information

See Arizona salary details

$35.4K

$108K

$178.5K

How much do learning engineer jobs pay per year?

As of Jul 8, 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 is a 900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as AI research directors, machine learning executives, or senior data scientists, often requiring advanced skills, extensive experience, and sometimes equity or performance-based compensation. These positions are usually found in leading tech companies or startups with significant AI investments and may involve managing teams, developing innovative algorithms, or overseeing AI strategy. Compensation at this level reflects the value of expertise in AI development, deployment, and strategic planning.

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.

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 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.

Will MLE be replaced by AI?

As a Learning Engineer, AI is a tool that can enhance machine learning workflows, but it is unlikely to fully replace the need for human expertise in designing, implementing, and maintaining machine learning systems. MLE roles require skills in data handling, model evaluation, and system deployment that go beyond automation. AI can automate certain tasks, but human oversight remains essential for ensuring ethical, effective, and reliable machine learning solutions.

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 engineer makes $500,000 a year?

Senior software engineers, especially those in high-demand fields like machine learning, AI, or working at major tech companies, can earn $500,000 or more annually through base salary, bonuses, and stock options. Achieving this level typically requires extensive experience, advanced skills, and often working in competitive markets or leadership roles.

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.
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 July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $107,973 per year, or $51.9 per hour.
Machine Learning Operations (MLOps) Engineer

Machine Learning Operations (MLOps) Engineer

Kforce Technology Staffing

Phoenix, AZ โ€ข On-site

$101K - $134K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 8 days ago


Job description

RESPONSIBILITIES:
Kforce has a client that is seeking a Machine Learning Operations (MLOps) Engineer (Snowflake) in Phoenix, AZ.
Summary:
We are seeking a Senior MLOps Engineer to help design and build an enterprise-scale machine learning platform from the ground up. This is a unique opportunity to establish a modern MLOps ecosystem on Snowflake, supporting end-to-end model development, deployment, and lifecycle management.
The platform will be built on a medallion architecture (Bronze, Silver, Gold), enabling machine learning models to consume trusted, governed data products with full lineage, scalability, and performance. This role will play a key part in shaping standards, processes, and tooling as the platform evolves from MVP to enterprise scale.
Key Responsibilities:
* Architect and build a production-grade MLOps platform on Snowflake, leveraging Snowpark, Snowflake ML, Model Registry, and Feature Store
* Design and operationalize reusable pipelines for training, validation, deployment, inference, and monitoring
* Align ML workflows with Bronze, Silver, and Gold medallion layers to ensure consistent use of trusted data
* Establish model lifecycle management standards, including versioning, approvals, promotion gates, and rollback strategies
* Partner with data scientists to productionize models into scalable, reliable services
* Implement model observability for performance, drift, bias, and data quality, with alerting and SLOs
* Automate retraining and refresh processes using Snowflake Tasks, Dynamic Tables, and event-driven orchestration
* Collaborate with data engineering teams to ensure reliable and reusable feature pipelines
* Define and implement CI/CD pipelines for ML systems, including testing frameworks and release controls
* Drive governance across security, compliance, auditability, reproducibility, and responsible AI practices
* Lead platform maturation, including documentation, developer enablement, and operational runbooks
REQUIREMENTS:
* 5+ years of experience in ML Engineering, MLOps, or platform engineering
* Strong Python and SQL skills, with experience building production ML pipelines
* Hands-on experience with Snowflake data platforms (Snowpark and Snowflake ML strongly preferred)
* Experience with model deployment, versioning, monitoring, and lifecycle governance
* Experience implementing CI/CD and testing strategies for ML systems
* Strong understanding of feature engineering, training-serving consistency, and data quality controls
* Experience working with cloud platforms (AWS preferred)
* Proven ability to collaborate across data science, data engineering, and business teams
Preferred Qualifications:
* Experience with Snowflake Model Registry and Feature Store
* Background in medallion/lakehouse data architectures
* Experience with dbt or similar transformation tools
* Familiarity with streaming or near real-time ML inference
* Experience in high-volume operational environments (e.g., logistics, fleet, routing)
* Prior experience building greenfield platforms and establishing standards from scratch
This role can be performed fully remotely but there is a preference for Phoenix local talent. This role has the potential to convert to FTE with Kforce's client.
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
By clicking ?Apply Today? you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.