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Generative Ai Engineer Intern Jobs in Arizona (NOW HIRING)

Principal AI Engineer

Tucson, AZ · On-site

$179K - $226K/yr

Assess and implement emerging technologies, including generative AI, foundation models, LLMs, AI ... Mentor engineers, scientists, and technical teams in AI technologies, architecture, and responsible ...

Principal AI Engineer

Tucson, AZ · On-site

$179K - $226K/yr

Assess and implement emerging technologies, including generative AI, foundation models, LLMs, AI ... Mentor engineers, scientists, and technical teams in AI technologies, architecture, and responsible ...

Assess and implement emerging technologies, including generative AI, foundation models, LLMs, AI ... Mentor engineers, scientists, and technical teams in AI technologies, architecture, and responsible ...

AI Engineer

Phoenix, AZ · On-site

$110K - $125K/yr

AI Engineer Overview: As an AI Business Engineer, your role will be that of a business embedded ... Generative AI. • Drive discovery sprints and AI ideation efforts • Stay abreast of broad AI ...

Job details Job Role Specialist Programmer Career Role Specialist Programmer Work Location Phoenix ... Design, develop, and deploy generative AI models for various applications, such as text generation ...

Showing results 21-40

Generative Ai Engineer Intern information

What does a generative AI engineer intern do?

A Generative AI Engineer Intern assists in developing and testing machine learning models, specifically those that can create new content such as text, images, or audio. They work with frameworks like TensorFlow or PyTorch, collaborate with senior engineers, and help improve the performance and reliability of generative AI systems. Interns may also be involved in data preprocessing, model evaluation, and keeping up with the latest research in artificial intelligence.

What skills and qualifications are needed to thrive as a generative AI engineer intern?

To thrive as a Generative AI Engineer Intern, you need a solid understanding of machine learning fundamentals, programming skills (especially in Python), and coursework or experience in artificial intelligence or computer science. Familiarity with deep learning frameworks like TensorFlow or PyTorch and version control systems such as Git is typically required, and relevant coursework or certifications in AI/ML are advantageous. Strong problem-solving skills, curiosity, and the ability to communicate complex ideas clearly help interns stand out. These skills and qualities are crucial for quickly learning advanced AI techniques, contributing to team projects, and driving innovation in a rapidly evolving field.

What types of projects can a generative AI engineer intern expect to work on during their internship?

As a Generative AI Engineer Intern, you can expect to work on projects involving the development, training, and evaluation of generative models such as GANs, VAEs, or transformer-based architectures. Typical tasks may include data preprocessing, model implementation, fine-tuning, and running experiments to improve model performance. Interns often collaborate closely with data scientists, software engineers, and research teams, gaining exposure to both research and application of AI in real-world products. This role provides hands-on experience with state-of-the-art tools and frameworks, offering a valuable foundation for a future career in AI engineering or research.

What is the difference between Generative Ai Engineer Intern vs Machine Learning Engineer Intern?

AspectGenerative Ai Engineer InternMachine Learning Engineer Intern
Required CredentialsBasic knowledge of AI, programming, and some coursework in machine learning or AIStrong foundation in machine learning, programming, and data analysis, often with coursework or certifications
Work EnvironmentTech companies, startups, research labs focusing on AI applicationsTech firms, research institutions, and companies applying machine learning models
Industry UsageDeveloping generative models like GPT, DALL·E, and similar AI toolsBuilding predictive models, data pipelines, and machine learning algorithms

While both roles involve AI and machine learning, a Generative Ai Engineer Intern focuses specifically on creating generative models like text, images, or audio, whereas a Machine Learning Engineer Intern works broadly on developing and deploying various machine learning algorithms across different applications.

What are the most commonly searched types of Generative Ai Engineer jobs in Arizona? The most popular types of Generative Ai Engineer jobs in Arizona are:
What job categories do people searching Generative Ai Engineer Intern jobs in Arizona look for? The top searched job categories for Generative Ai Engineer Intern jobs in Arizona are:
What cities in Arizona are hiring for Generative Ai Engineer Intern jobs? Cities in Arizona with the most Generative Ai Engineer Intern job openings:
Infographic showing various Generative Ai Engineer Intern job openings in Arizona as of August 2026, with employment types broken down into 17% Internship, 66% Full Time, and 17% Part Time. Highlights an 100% In-person job distribution.

$179 - $226/hr

Other

Posted 2 days ago

New


Job description

NOIRLab is seeking an accomplished Principal AI Engineer to define and lead the organization's artificial intelligence strategy, technical architecture, and AI engineering capabilities. This highly visible leadership role will establish the foundational AI platforms, engineering practices, and governance framework that enable scientists, software engineers, and operations teams to harness the power of artificial intelligence in support of groundbreaking astronomical research and observatory operations.

As NOIRLab's first dedicated AI engineering leader, you will have a unique opportunity to shape how AI is adopted across one of the world's premier astronomical research organizations. You will identify and prioritize high-impact AI opportunities, build enterprise-scale AI capabilities, and deliver innovative solutions that accelerate scientific discovery, increase engineering productivity, and improve operational efficiency.

This role combines strategic vision with hands-on technical leadership. You will partner closely with researchers, software engineers, data scientists, and operational stakeholders to design, prototype, implement, and deploy production-ready AI systems. The ideal candidate is equally comfortable defining long-term AI strategy, architecting scalable AI platforms, and personally contributing to the development of advanced AI solutions.

At NOIRLab, we believe scientific discovery and technological innovation go hand in hand. We value intellectual curiosity, continuous learning, and a passion for solving complex problems. This position offers the rare opportunity to apply cutting-edge AI technologies—including machine learning, generative AI, large language models (LLMs), advanced analytics, and agentic systems—to help answer fundamental questions about our universe while advancing the future of scientific computing.

If you are energized by the challenge of building AI capabilities from the ground up and motivated by the potential to make a lasting impact on science, this is an exceptional opportunity to lead transformative innovation at a global research institution.

Key ResponsibilitiesAI Strategy & Technical Leadership
  • Define and execute NOIRLab's enterprise AI strategy, technical vision, and multi-year roadmap aligned with scientific, engineering, and operational goals.
  • Identify, evaluate, and prioritize high-value AI use cases that deliver measurable business and scientific impact.
  • Establish AI engineering standards, development methodologies, reusable frameworks, and best practices that support scalable adoption across the organization.
  • Assess and implement emerging technologies, including generative AI, foundation models, LLMs, AI agents, and advanced machine learning approaches.
  • Develop governance frameworks, model evaluation processes, and lifecycle management practices that ensure responsible, secure, and effective AI deployment.
  • Establish key performance indicators (KPIs) and success metrics to evaluate the effectiveness of AI initiatives.
  • Design and implement secure, scalable, and production-ready AI platforms and applications that integrate with scientific research systems, software platforms, and operational workflows.
  • Lead the development of LLM-powered applications, Retrieval-Augmented Generation (RAG) systems, AI agents, copilots, and other advanced AI solutions.
  • Establish platform capabilities that enable experimentation, model deployment, monitoring, observability, and continuous improvement.
  • Partner with IT and enterprise technology teams to ensure AI systems meet organizational requirements for reliability, scalability, security, and compliance.
Advanced Analytics & Scientific Computing
  • Develop advanced analytics capabilities that support scientific discovery, operational decision-making, and organizational effectiveness.
  • Apply machine learning, statistical modeling, and AI techniques to large-scale scientific datasets and computational workflows.
  • Evaluate and optimize model performance, accuracy, explainability, and operational effectiveness.
  • Collaborate with researchers and technical teams to leverage AI in solving complex scientific and engineering challenges.
Technical Leadership & Cross-Functional Collaboration
  • Serve as the organization's senior technical authority for AI, machine learning, and advanced analytics.
  • Mentor engineers, scientists, and technical teams in AI technologies, architecture, and responsible AI practices.
  • Collaborate across scientific, engineering, and operations organizations to drive AI adoption and innovation.
  • Engage with external research institutions, observatories, and scientific communities to promote collaboration, interoperability, and knowledge sharing.
  • Foster a culture of experimentation, continuous improvement, and responsible innovation.
What You'll BringRequired Qualifications
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related technical field, or equivalent combination of education and experience.
  • 15+ years of experience in software engineering, artificial intelligence, machine learning, or related fields, including experience serving as a Principal Engineer, AI Technical Lead, Architect, or equivalent senior technical leadership role.
  • Demonstrated success designing, building, and deploying production-scale AI and machine learning solutions.
  • Deep expertise in machine learning, generative AI, large language models, modern AI architectures, and AI engineering best practices.
  • Experience developing and deploying LLM applications, RAG systems, AI agents, and foundation model-based solutions.
  • Strong background in cloud-native architecture, distributed systems, data platforms, and AI infrastructure.
  • Experience implementing AI operationalization practices, including model deployment, monitoring, evaluation, governance, and lifecycle management.
  • Expertise in secure, responsible AI development and model governance frameworks.
  • Advanced software engineering skills and proficiency with modern programming languages, frameworks, and AI development ecosystems.
  • Exceptional communication, leadership, and collaboration skills with the ability to influence diverse technical and non-technical stakeholders.
Preferred Qualifications
  • Experience applying AI, machine learning, or advanced analytics within scientific research environments.
  • Familiarity with astronomical datasets, observatory operations, scientific instrumentation, or related research domains.
  • Experience with high-performance computing (HPC), large-scale data processing, or scientific computing platforms.
  • Contributions to open-source software, AI frameworks, or scientific computing communities.
  • Experience building organizational AI capabilities and driving enterprise-wide AI adoption strategies.

Salary Range: $179,000-$226,000 . The final salary will depend on skills, qualifications, experience and job location.

This position will remain open until it is filled.

Why Join NOIRLab?
  • Lead the AI vision for one of the world's leading astronomical research organizations.
  • Build AI capabilities from the ground up with executive visibility and organizational influence.
  • Apply cutting-edge AI technologies to accelerate scientific discovery and innovation.
  • Collaborate with world-class scientists, engineers, and researchers solving some of humanity's most fundamental questions.
  • Make a lasting impact on both the future of AI and our understanding of the universe.

Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws.For further information, please review the Know Your Rights notice from the Department of Labor.

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