1

Learning Ai Jobs in Arizona (NOW HIRING)

AI & Machine Learning Engineer

Chandler, AZ ยท On-site

$100K - $110K/yr

Design, develop, and deploy AI-powered healthcare applications using Large Language Models (LLMs), Machine Learning, and Generative AI * Build intelligent agents, RAG solutions, prompt workflows, and ...

S., Ascend Learning was recognized by Newsweek and Plant-A Insights Group as one of America's 2025 ... WHAT YOU'LL DO NASM is seeking a Director of Data and AI , reporting to the Chief Information ...

Director Data & AI

Gilbert, AZ ยท On-site

$171 - $244/hr

S., Ascend Learning was recognized by Newsweek and Plant-A Insights Group as one of America's 2025 ... WHAT YOU'LL DO NASM is seeking a Director of Data and AI , reporting to the Chief Information ...

No prior AI experience is required. Key Responsibilities * Create reinforcement learning environments for software engineering tasks. * Design tasks involving bug fixing, feature development ...

AI Trainer - Remote

Phoenix, AZ ยท Remote

$80 - $120/hr

No prior AI experience is required. Key Responsibilities ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

New

AI Engineer - Remote

Phoenix, AZ ยท Remote

$80 - $120/hr

No prior AI experience is required. Key Responsibilities ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

next page

Showing results 1-20

Learning Ai information

What is a learning AI?

A Learning AI, or Artificial Intelligence that learns, refers to computer systems that can improve their performance over time by analyzing data and experiences. These systems use techniques such as machine learning and deep learning to adapt to new information, recognize patterns, and make predictions or decisions without being explicitly programmed for every task. Learning AI is used in many applications, including recommendation engines, language translation, and autonomous vehicles. As technology advances, Learning AI continues to play a crucial role in automating complex tasks and enhancing decision-making processes.

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

To thrive as a Learning AI Engineer, you need a solid background in computer science, mathematics, and machine learning, often supported by a relevant degree or certification. Familiarity with programming languages like Python, machine learning libraries (such as TensorFlow or PyTorch), and cloud computing platforms is typically required. Strong problem-solving skills, adaptability, and effective communication set outstanding professionals apart in this field. These skills are crucial for building, deploying, and refining AI models that solve real-world problems efficiently and ethically.

How do learning AI professionals typically collaborate with subject matter experts to develop effective training solutions?

Learning AI professionals frequently work alongside subject matter experts (SMEs) to ensure that AI-driven training tools and content are accurate, relevant, and engaging. This collaboration often involves regular meetings to gather domain-specific knowledge, iterative review of training modules, and feedback sessions to fine-tune AI models for optimal learning outcomes. Clear communication and a strong partnership with SMEs are essential, as they help bridge technical AI capabilities with real-world educational needs, resulting in more impactful and user-friendly learning solutions.

What is the difference between Learning Ai vs Data Scientist?

AspectLearning AiData Scientist
Required CredentialsTypically a degree in Computer Science, AI, or related fields; certifications in AI/MLDegree in Computer Science, Statistics, or related fields; certifications in data analysis or ML
Work EnvironmentTech companies, AI startups, research labs focusing on AI developmentBusiness environments, analyzing data to inform decisions across industries
Employer & Industry UsagePrimarily in AI development, research, and product creationAcross finance, healthcare, marketing, and other sectors for data analysis

Learning Ai focuses on developing algorithms and models that enable machines to learn and improve autonomously, often involving deep learning and neural networks. Data Scientists analyze and interpret complex data to help organizations make informed decisions. While both roles require knowledge of machine learning, Learning Ai is more centered on creating AI systems, whereas Data Scientists focus on extracting insights from data.

How do I start a career in learning ai?

To start a career in learning AI, develop a strong foundation in mathematics, programming (especially Python), and machine learning concepts. Gaining hands-on experience through projects, online courses, and certifications such as those from Coursera or edX can help build skills and demonstrate expertise to employers.

Is learning AI a good career path?

Learning AI can be a strong career choice due to high demand for skills in machine learning, data analysis, and programming languages like Python. Careers in AI often require continuous learning, strong problem-solving skills, and familiarity with tools such as TensorFlow or PyTorch. The field offers opportunities across industries including technology, healthcare, finance, and automotive sectors.

What are popular job titles related to Learning Ai jobs in Arizona?

For Learning Ai jobs in Arizona, the most frequently searched job titles are:

What cities in Arizona are hiring for Learning Ai jobs?

Cities in Arizona with the most Learning Ai job openings:

Staff / Principal AI Engineer

Gilbert, AZ โ€ข On-site

$170K - $190K/yr

Other

Dental, Vision, Retirement

Posted 6 days ago


Job description

Vaco is partnering with a growing education technology organization to hire a Staff / Principal AI Engineer to help define and build the next generation of AI-powered products, platforms, and internal capabilities. This is a highly visible, hands-on technical leadership role focused on bringing practical AI innovation into both customer-facing products and internal business operations.

This person will serve as a technical change leader as the organization moves toward broader use of AI agents, generative AI, machine learning, and LLM-powered product experiences. The right candidate will bring strong architecture and engineering depth, but also a product mindset. This role is about building real solutions, teaching teams how to use AI effectively, securing AI-enabled workflows, and identifying where AI can improve customer experience, training products, marketing funnels, and business outcomes.

What Youโ€™ll Be Doing
  • Lead the design, development, and deployment of scalable AI and machine learning solutions across product and internal business use cases
  • Architect generative AI systems, LLM-powered workflows, agentic solutions, and AI-enabled product features
  • Build and optimize LLMOps pipelines that support reliable deployment, evaluation, monitoring, and iteration of AI models
  • Partner with product, architecture, data, engineering, innovation, and marketing teams to identify where AI can create measurable business impact
  • Drive AI innovation within customer-facing products, training platforms, digital experiences, and lead conversion workflows
  • Evaluate and implement approaches for prompt engineering, context management, embeddings, retrieval, and model optimization
  • Design AI systems with feedback loops, automated retraining, fine-tuning, and lifecycle management where appropriate
  • Build data pipelines and preprocessing workflows that ensure data quality, security, and regulatory alignment
  • Provide hands-on technical leadership through architecture reviews, code contributions, proof-of-concepts, and implementation guidance
  • Mentor AI engineers and partner with architects across application, product, CRM, and data domains
  • Help establish standards, documentation, and best practices for responsible AI development and deployment
  • Stay current on emerging AI trends, including AIโ€™s impact on digital marketing, Answer Engine Optimization, Generative Engine Optimization, and customer discovery behavior
Required Experience
  • 8 or more years of progressive experience across software engineering, data, analytics, machine learning, AI engineering, or related technology roles
  • 1 or more years of experience developing and implementing analytical, AI, or machine learning applications
  • Hands-on experience building and deploying LLM-based solutions, generative AI applications, or AI-powered product features
  • Strong understanding of machine learning, natural language processing, large language models, embeddings, retrieval patterns, and model evaluation
  • Experience with Python, SQL, Hugging Face, Snowflake, and modern ML or analytics tooling
  • Experience designing AI or ML solutions in Azure or comparable cloud environments
  • Experience with CI/CD pipelines, Docker, Kubernetes, MLflow, or similar MLOps and lifecycle management tools
  • Ability to translate ambiguous AI opportunities into practical, scalable engineering solutions
  • Strong product mindset with interest in customer experience, product innovation, marketing enablement, and business impact
  • Demonstrated ability to mentor engineers, influence technical direction, and guide best practices
  • Strong communication skills with the ability to present complex AI concepts to technical and non-technical stakeholders
  • Bachelorโ€™s degree in Computer Science, Artificial Intelligence, or a related field preferred, or equivalent professional experience
Nice to Have
  • Experience building AI agents or agentic workflows for internal business operations
  • Exposure to AI security, responsible AI, model governance, or securing AI-enabled systems
  • Experience applying AI to online shopping, customer acquisition, digital marketing, or lead conversion workflows
  • Familiarity with Answer Engine Optimization or Generative Engine Optimization concepts
  • Experience with Azure AI services or comparable cloud AI platforms
  • Background working in education technology, training platforms, eCommerce, or digital learning environments
  • Experience helping organizations adopt AI tools, workflows, and operating models across multiple teams
Compensation & Benefits
  • Salary range: $170,000 to $190,000 annually
  • Full-time role with benefits package available
 

If you are a hands-on AI engineering leader who wants to build practical generative AI systems, shape product innovation, and help an organization move from AI experimentation to real enterprise adoption, we would welcome the opportunity to connect.


Determining compensation for this role (and others) at Vaco/Highspring depends upon a wide array of factors including but not limited to the individualโ€™s skill sets, experience and training, licensure and certifications, office location and other geographic considerations, as well as other business and organizational needs. With that said, as required by local law in geographies that require salary range disclosure, Vaco/Highspring notes the salary range for the role is noted in this job posting. The individual may also be eligible for discretionary bonuses, and can participate in medical, dental, and vision benefits as well as the companyโ€™s 401(k) retirement plan. Additional disclaimer: Unless otherwise noted in the job description, the position Vaco/Highspring is filing for is occupied. Please note, however, that Vaco/Highspring is regularly asked to provide talent to other organizations. By submitting to this position, you are agreeing to be included in our talent pool for future hiring for similarly qualified positions. Submissions to this position are subject to the use of AI to perform preliminary candidate screenings, focused on ensuring minimum job requirements noted in the position are satisfied. Further assessment of candidates beyond this initial phase within Vaco/Highspring will be otherwise assessed by recruiters and hiring managers. Vaco/Highspring does not have knowledge of the tools used by its clients in making final hiring decisions and cannot opine on their use of AI products.