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Associate Artificial Intelligence Machine Learning Jobs in Arizona

AI Solutions Architect

Tempe, AZ · On-site

$61.25 - $80.75/hr

... artificial intelligence and machine learning engagements while collaborating with various ... Engineer Associate, Microsoft Azure Data Scientist Associate, or Microsoft Azure Solutions ...

AI Solutions Architect

Tempe, AZ · On-site

$60.25 - $79.50/hr

Leading sales, solution design, and delivery for artificial intelligence, machine learning ... Engineer Associate, Microsoft Azure Data Scientist Associate, or Microsoft Azure Solutions ...

Applying artificial intelligence, machine learning, and data engineering methods to cybersecurity use cases such as detection engineering, threat hunting, and response acceleration * Working with ...

Artificial Intelligence Sr. Manager/Director

Phoenix, AZ · On-site

$231K - $242K/yr

Artificial Intelligence Sr. Manager/Director Locations: AZ - Phoenix, CO - Denver, TX - Austin ... Minimum 7 years hands on machine learning experience * Minimum 5 years experience with at least one ...

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Associate Artificial Intelligence Machine Learning information

What are the key skills and qualifications needed to thrive as an Associate Artificial Intelligence Machine Learning professional, and why are they important?

To thrive as an Associate Artificial Intelligence Machine Learning professional, you need a solid background in mathematics, statistics, and computer science, typically with a relevant degree and familiarity with machine learning concepts. Proficiency in programming languages like Python or R, experience with frameworks such as TensorFlow or PyTorch, and knowledge of version control systems are commonly required. Strong problem-solving, analytical thinking, and effective communication skills help differentiate top performers in this role. These skills are crucial for developing accurate models, collaborating with multidisciplinary teams, and driving impactful AI solutions.

What is the difference between Associate Artificial Intelligence Machine Learning vs Data Scientist?

AspectAssociate Artificial Intelligence Machine LearningData Scientist
Required CredentialsBachelor's in CS, AI, or related; certifications in ML/AIBachelor's/Master's in CS, Statistics, or related; often advanced degrees
Work EnvironmentTech companies, R&D labs, startupsData-driven organizations, consulting firms, tech companies
Employer & Industry UsageAI/ML teams, product developmentData analysis, predictive modeling, business insights
Common Search & ComparisonYesYes

Associate Artificial Intelligence Machine Learning roles focus on developing and implementing AI/ML models, often with entry-level responsibilities. Data Scientists analyze data to extract insights, build predictive models, and support decision-making. While both roles require knowledge of programming and statistics, Data Scientists typically have more advanced degrees and focus on data analysis, whereas Associate AI/ML roles are more specialized in AI/ML model development.

What does an Associate Artificial Intelligence Machine Learning professional do?

An Associate Artificial Intelligence Machine Learning (AI/ML) professional assists with the development, testing, and deployment of AI and machine learning models. They typically work under the supervision of senior data scientists or machine learning engineers, helping to preprocess data, select algorithms, and evaluate model performance. Their responsibilities may also include writing code, analyzing results, and supporting the integration of models into applications or systems. This entry-level role is ideal for those who have foundational knowledge in AI/ML concepts and are looking to gain practical, hands-on experience in the field.

What are some common challenges faced by Associate Artificial Intelligence Machine Learning professionals in their first year, and how can they overcome them?

Associate AI/ML professionals often encounter challenges such as understanding complex datasets, adapting to rapidly evolving tools and frameworks, and bridging the gap between theoretical knowledge and practical application. Collaborating closely with senior team members, seeking mentorship, and participating in code reviews are effective ways to overcome these challenges. Additionally, staying updated with industry trends and continuously practicing model building on real-world problems can help associates gain confidence and accelerate their learning curve.
What are the most commonly searched types of Artificial Intelligence Machine Learning jobs in Arizona? The most popular types of Artificial Intelligence Machine Learning jobs in Arizona are:
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Hybrid Visiting Professor of Artificial Intelligence

devry

Phoenix, AZ

Other

Posted 28 days ago


Job description

Opportunity:
DeVry University focuses on developing long-term relationships with superior instructors who have high professional standards, excellent communication skills, enthusiasm and a commitment to providing the finest practitioner-focused education. We are seeking primarily industry professionals to teach and share their knowledge and experience with undergraduate and graduate students in a variety of fields.

  • Courses meet once or twice a week for eight weeks.
  • Face-to-face interaction is blended with technology (such as online discussions and online assignments) for an enhanced learning environment.
  • Faculty are responsible for facilitating student learning by teaching courses and programs in accordance with DeVry University requirements.
  • Faculty develop course syllabi and lesson plans and apply teaching techniques to best achieve course and programmatic objectives.
  • All DeVry instructors will participate in a comprehensive faculty training program and ongoing faculty development activities to ensure the highest quality instruction. 
  • DeVry University does not guarantee any specific number of work hours or assignments, which may vary based on the University’s needs and discretion.
  • As you explore this opportunity, we invite you to view this brief video highlighting how our faculty engage in meaningful student support.

Responsibilities:

  • Develops and provides students with an approved DeVry University syllabus that follows a template established by the local campus, and which includes the terminal course objectives.
  • Organizes, prepares, and regularly revises and update all course materials.
  • Uses appropriate technological options for online technologies and course-related software, including Websites, e-mail, and online discussions for preparing the course and making it accessible to students.
  • Models effective oral and written communications that engage the students, provide clarity, and improve student learning.
  • Sets clear expectations for the course by publishing course terminal objectives, assignment/examinations dates, and weight the distribution of various evaluation categories.
  • Ensures that the content and level of material included on exams correspond to the course terminal objectives.
  • Demonstrates consistency and fairness in the preparation and grading of exams, and provide timely feedback to students.
  • Embraces and integrates the responsible use of AI technologies in the classroom to enhance teaching and learning outcomes.
  • Demonstrates the ability to recognize, evaluate, and address appropriate and inappropriate student use of AI tools in academic work.
  • Completes other duties as assigned.

Qualifications:

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

  •  A doctorate in Artificial Intelligence, Computer Science, Data Science, Information Systems, or a closely related field is required, with at least 18 graduate credit hours in artificial intelligence, machine learning, data science, or a related computational discipline. 
    • Applicants must upload unofficial graduate-level and above transcripts with their application.
  • Degrees must be awarded by an institution accredited by an agency recognized by the U.S. Department of Education or the Council for Higher Education Accreditation, or by an international institution determined to hold equivalent accreditation.
  • Three to five years of applied professional experience in artificial intelligence, machine learning, data science, intelligent systems, or related computational technologies.
  • Demonstrated experience with AI-enabled software development, which may include machine learning pipelines, generative AI tools, data modeling, or full-stack application development integrating AI services.
  • Two to five years of teaching experience at the post-secondary level, preferably in artificial intelligence, data science, programming, or emerging technology disciplines.
  • Industry-recognized certifications or professional credentials relevant to artificial intelligence, machine learning, data science, or software development.
  • Strong subject matter expertise in AI concepts and technologies, combined with effective communication skills and the ability to explain complex technical topics to diverse learners.
  • Knowledge of ethical, responsible, and secure AI practices, including awareness of data governance, bias mitigation, and responsible AI deployment.
  • Additional requirements driven by state licensing, institutional policy, or accreditation standards may apply.

Preferred Qualifications

  • Industry certifications in Python programming, artificial intelligence, machine learning, or data science (e.g., PCEP or equivalent).
  • AI practitioner or engineer certifications (e.g., CAIP, Oracle GenAI, or comparable industry-recognized credentials).
  • Experience with AI development frameworks and tools, such as machine learning libraries, model deployment platforms, or generative AI systems.
  • Experience applying DevSecOps practices in AI or data-driven environments, including model lifecycle management and secure AI deployment.
  • Experience with programmatic or regional accreditation processes, including outcomes assessment and curriculum alignment.
  • Active membership or engagement in professional technology or AI-related organizations, contributing to ongoing industry awareness and innovation.
  • Experience integrating AI-assisted learning tools, immersive technologies, or intelligent tutoring systems into post-secondary instruction.

Pay:

Visiting Professor pay is based on level, credit hours taught per 8-week session, and location. 

  • Pay may vary in most states from $1500-$2700 per 8-week session.
  • Pay in the states of AZ, CA, IN and PA is paid at an hourly rate of either $22.00/hour or $23.50/hour.Â