15 AI Internships for Undergraduates in Alaska
Internships are a practical way to build experience while you are still in college. They help you understand how classroom learning connects to real-world work environments. You will also develop technical skills, communication ability, and confidence in applying what you study. For students interested in Artificial Intelligence, internships can help you understand how machine learning models, algorithms, and data-driven tools are actually used in real industries. Many employers prefer candidates who already have project experience, and internships are often the easiest way to demonstrate this.
Check out other AI interships available for undergraduates here.
Why should I do an Artificial Intelligence internship in college?
If you are studying computer science, data science, or engineering, doing an AI internship during college can significantly strengthen your academic profile. AI internships help you apply theoretical concepts like neural networks, natural language processing, and predictive modeling in real-world environments. This kind of experience can make your resume more competitive when applying for full-time roles or graduate school. During internships, you’ll often work with real datasets, collaborate with engineers, and solve practical problems. Many also connect you with faculty researchers, engineers, or industry professionals, helping you understand industry expectations and research workflows.
We have narrowed down this list of 15 AI internships for undergraduates in Alaska based on factors like mentorship quality, research exposure, selectivity, and real-world skill development.
1. NASA Summer Internship (via Alaska Space Grant Program)
Location: NASA Centers (U.S.) + Alaska sponsorship via Alaska Space Grant Program
Cost/Stipend: Up to $8,200 + $1,000 travel stipend
Acceptance rate/cohort size: Highly competitive (nationwide selection)
Dates: June – August
Application Deadline: February 27 (NASA); March 1 (ASGP Sponsorship)
Eligibility: Undergraduate students in STEM fields; U.S. citizens with a minimum 3.0 GPA
During this internship, you will work on advanced projects involving artificial intelligence, machine learning, robotics, or data science, depending on the specific placement. You will contribute to research areas such as autonomous systems, satellite imaging analysis, or predictive modeling for space missions. You will collaborate with experienced engineers and researchers, gaining exposure to high-level scientific workflows. The internship also includes professional development sessions that help you understand career pathways in aerospace and AI research. Through the Alaska Space Grant sponsorship, students from Alaska can access national-level opportunities while maintaining local academic connections.
2. Ladder Internship Program
Location: Virtual
Cost/Stipend: Varies; Financial aid is available
Acceptance rate/cohort size: Selective
Dates: Multiple cohorts throughout the year
Application Deadline: Rolling
Eligibility: Students able to work 10–20 hours/week
Ladder connects students with startups working on projects across AI, machine learning, and emerging technologies. You work with startup teams on real projects while receiving guidance from a program mentor. The structure allows you to contribute to tasks like research, product development, or technical analysis. You also present your work at the end of the internship. Exposure to startup workflows helps you understand innovation cycles and product design. Collaboration with founders provides insight into entrepreneurship. This program offers practical experience aligned with AI internships for undergraduates in Alaska in a remote format.
3. AI-UNITE Internship Program
Location: University of Alaska Anchorage
Cost/Stipend: Funded internships available
Acceptance rate/cohort size: Not publicly disclosed
Dates: Year-round
Application Deadline: Rolling
Eligibility: Undergraduate STEM students
AI-UNITE is one of the few AI-focused initiatives specifically based in Alaska, making it highly relevant for local students. You will work on applied AI projects connected to real-world challenges in healthcare, public systems, and energy. The program emphasizes ethical AI development and responsible data usage. Through mentorship from faculty and industry collaborators, you’ll gain insight into interdisciplinary AI applications. Many projects involve machine learning, predictive modeling, or data analysis techniques. The program also encourages collaboration with other researchers across the state.
4. Alaska Center for Energy and Power (ACEP) Summer Internship
Location: University of Alaska Fairbanks
Cost/Stipend: Paid internship + travel + housing
Acceptance rate/cohort size: Selective
Dates: June 1 – August 7
Application Deadline: January 23
Eligibility: Undergraduate STEM students
ACEP provides applied research experience where AI and data science intersect with sustainability and energy systems. You may work on projects related to renewable energy forecasting, microgrid optimization, or energy data analysis. The program includes one-on-one mentorship and structured research training. You also participate in collaborative workshops and field visits to understand how technology is used in real infrastructure. The interdisciplinary focus helps you understand how AI supports environmental and engineering solutions. Interns often gain experience using computational tools for real-world challenges.
5. Computer Science & Engineering Internship Program (CSCE A395)
Location: University of Alaska Anchorage
Cost/Stipend: Varies
Acceptance rate/cohort size: Open enrollment
Dates: Year-round
Application Deadline: Rolling
Eligibility: Undergraduate Computer Science students
This program allows you to gain internship experience while earning academic credit through structured reporting and supervision. You are responsible for securing a technical internship, often involving AI, machine learning, or software development. The university supports the process through career services and employer partnerships. You’ll complete structured academic assignments, including reports and presentations. Many students work on projects involving data analysis or algorithm development. The program bridges classroom learning with professional application. It provides flexible pathways into AI internships for undergraduates in Alaska.
6. Yale University Computer Science Research Internship Program
Location: Virtual
Cost/Stipend: Varies
Acceptance rate/cohort size: Highly selective
Dates: Typically Summer
Application Deadline: December 15 (recommended)
Eligibility: Undergraduate students in Computer Science or related fields
This research internship connects you directly with faculty working on advanced artificial intelligence topics. You may work on projects related to deep learning, natural language processing, or computational modeling, depending on faculty research interests. The structure is flexible, allowing projects to align with your academic background and goals. You’ll gain experience designing experiments, implementing models, and analyzing research outcomes. You could also contribute to academic publications or ongoing research initiatives. The mentorship structure encourages independent thinking and technical exploration.
7. UMBC NSF-REU in Online Interdisciplinary Big Data Analytics
Location: Virtual
Cost/Stipend: Paid stipend
Acceptance rate/cohort size: Selective
Dates: June 9 – August 1 (Tentative)
Application Deadline: February
Eligibility: Undergraduate STEM students
This research internship focuses on applying machine learning and data science techniques across scientific disciplines. You’ll work on projects involving large datasets in fields such as engineering, atmospheric science, or medicine. You will have mentorship from faculty specializing in mathematics and information systems. Throughout the internship, you’ll learn high-performance computing techniques and analytical workflows. The program includes seminars and final presentations where you share research outcomes. You’ll gain exposure to interdisciplinary collaboration and computational problem-solving. It is a strong remote option within AI internships for undergraduates in Alaska interested in data science.
8. Algoverse AI Research Program
Location: Virtual
Cost/Stipend: $3,325 program fee
Acceptance rate/cohort size: Selective
Dates: 12-week cohorts
Application Deadline: Rolling
Eligibility: Undergraduate students with Python experience
Algoverse offers structured mentorship where you’ll develop an original AI research project from concept to paper. You will work in small teams and follow a structured workflow that includes literature review, experimentation, and model development. Throughout the program, mentors guide you through research design and academic writing techniques. The program emphasizes reproducible results and publication-quality output. You also gain experience using collaborative tools and machine learning frameworks. This structured approach helps you understand the full lifecycle of AI research.
9. Allen Institute for AI (AI2) Research & Engineering Internships
Location: Hybrid (Seattle + remote flexibility)
Cost/Stipend: Paid internship
Acceptance rate/cohort size: Highly selective
Dates: Typically 12 weeks (summer)
Application Deadline: Fall
Eligibility: Undergraduate juniors and seniors in AI-related fields
AI2 offers strong exposure to both applied AI research and engineering development in real-world environments. You’ll work closely with experienced researchers on projects related to natural language processing, reasoning systems, and machine learning infrastructure. Engineering interns focus on implementing scalable AI systems, while research interns contribute to experimental design and analysis. Throughout the internship, you’ll collaborate with interdisciplinary teams to solve technical challenges. The program encourages independent problem-solving while still providing structured mentorship. Interns often contribute to tools or frameworks used in real AI products.
10. Vector Institute Research Internship Program (AI)
Location: Virtual
Cost/Stipend: Paid internship
Acceptance rate/cohort size: Highly selective
Dates: May – August / September – December / January – April
Application Deadline: November – January (summer cycle)
Eligibility: Undergraduate students (2nd year+) with machine learning experience
This internship allows you to work with researchers contributing to some of the most advanced developments in artificial intelligence. You are matched with faculty mentors and collaborate on research projects involving computer vision, reinforcement learning, and generative AI. During the program, you’ll gain hands-on experience designing models, analyzing datasets, and improving algorithm performance. The mentorship component helps you better understand research methodology and academic publishing workflows. You will also interact with industry professionals through structured networking initiatives. The program environment encourages collaboration and experimentation across interdisciplinary domains.
11. Generative AI: How to Use It and Why It Matters (Harvard Kennedy School)
Location: Virtual
Cost/Stipend: $1,995
Acceptance rate/cohort size: Open enrollment
Dates: May 11 – June 19
Application Deadline: April 27
Eligibility: Undergraduate students interested in AI
This program introduces you to generative AI concepts through applied exercises and case-based learning. You’ll explore neural networks, prompt engineering, and real-world applications of generative AI tools. The curriculum includes live sessions and interactive discussions with faculty. You’ll also build an AI-powered tool or prototype as part of the coursework. The program focuses on understanding both technical and societal implications of AI systems. You will gain insight into how AI influences policy, business, and innovation.
12. AI in Action: Organizational Strategy for Responsible Adoption of AI
Location: Virtual
Cost/Stipend: $2,495
Acceptance rate/cohort size: Open enrollment
Dates: May 11 – May 22
Application Deadline: April 27
Eligibility: Undergraduate students interested in AI strategy
This short program focuses on understanding how organizations implement artificial intelligence systems responsibly. You will study AI strategy, risk assessment, and real-world implementation challenges. There will be case studies that will help you analyze successful and failed AI adoption examples. You’ll also explore ethical considerations related to automation and decision-making systems. The program emphasizes collaboration and strategic thinking rather than technical development. You’ll develop a conceptual roadmap for implementing AI in organizations.
13. Competing in the Age of AI (Harvard Business School)
Location: Virtual
Cost/Stipend: $7,250
Acceptance rate/cohort size: Open enrollment
Dates: September 24 – November 19
Application Deadline: Rolling
Eligibility: Undergraduate students interested in AI strategy
This program focuses on how artificial intelligence is transforming business models and competitive strategy. You’ll learn how companies integrate AI into decision-making processes and operational workflows. There will be case-based learning to help you understand how organizations build AI-driven infrastructure. The program also explores ethical implications and long-term industry impact. You’ll analyze examples of companies implementing AI successfully. Discussions focus on balancing innovation with risk management. This strategic understanding can strengthen your perspective as you pursue AI internships for undergraduates in Alaska.
14. AI Essentials for Business (Harvard Business School Online)
Location: Virtual
Cost/Stipend: $1,850
Acceptance rate/cohort size: Open enrollment
Dates: Self-paced (~4 weeks)
Application Deadline: Rolling
Eligibility: Undergraduate students interested in AI fundamentals
This course introduces core artificial intelligence concepts with a focus on business applications. You’ll learn about predictive analytics, machine learning basics, and AI-driven decision systems. The curriculum includes real-world examples of AI adoption across industries. Ethical considerations and implementation risks are also discussed. The flexible format allows you to learn at your own pace. By the end, you understand how AI contributes to innovation strategies.
15. Data Science: Building Machine Learning Models (edX)
Location: Virtual
Cost/Stipend: Free to audit; $149 certificate option
Acceptance rate/cohort size: Open enrollment
Dates: Self-paced (~8 weeks)
Application Deadline: Rolling
Eligibility: Undergraduate students interested in machine learning
This course focuses on the practical foundations of machine learning through applied exercises. You’ll learn how predictive models are built and evaluated using real datasets. The curriculum covers concepts such as cross-validation and overfitting prevention. A key project involves building a recommendation system to help you understand algorithm performance. The hands-on structure makes complex ideas easier to understand. You also develop familiarity with machine learning workflows and experimentation methods.