15 Machine Learning Research Internships for Undergraduates

If you are an undergraduate student interested in machine learning, an internship can be a worthwhile way to explore this field. Internships connect classroom learning with research and professional work. For college students interested in machine learning, research internships can strengthen resumes and graduate school applications by demonstrating technical skills, project experience, and the ability to work in structured environments. Machine learning research internships for undergraduates provide experience with data analysis, AI/ML models, and multidisciplinary research practices. Along the way, you develop practical skills such as coding in Python, explaining technical results, and collaborating with research teams.

What machine learning research internships are available for undergraduates?

Machine learning research internships provide undergraduates with the opportunity to observe how algorithms are designed, trained, and evaluated in academic labs, national research institutions, and industry research groups. The programs in this list include opportunities to work on areas such as computer vision, natural language processing, robotics, foundation models, and large-scale data analysis, often under the guidance of faculty researchers or senior engineers. You can expect to participate in structured research projects, attend technical seminars or lab meetings, and present your findings through reports and final presentations. 

To help you get started, we’ve put together 15 machine learning internships for undergraduates that emphasize mentorship, technical skill development, and research experience you can use in future applications.

1. Microsoft Undergraduate Research Internship

Location: Microsoft research labs in Redmond, WA, New York City, NY, or New England, MA
Cost/Stipend: Free | benefits include competitive pay, possible relocation, training, transportation, and more
Acceptance rate/cohort size: Not specified
Dates: 12 weeks starting in May
Application Deadline: October 6 (tentative; subject to change)
Eligibility: Rising college juniors or seniors with majors in computer science, computer engineering, software engineering, information science, or a related major | must have at least two years of programming experience, completed courses in calculus, probability and statistics, and/or machine learning, or demonstrated training in at least one social science methodology

The Microsoft Undergraduate Research Internship is a full-time, paid 12-week summer research experience for rising juniors and seniors interested in computing and machine learning research. You will be placed in a U.S.-based Microsoft Research lab, where you will work on a defined research project in areas such as artificial intelligence, computer vision, natural language technologies, data analytics, security, or software engineering. Throughout the internship, you will collaborate closely with Microsoft researchers, doctoral students, and other interns while applying programming, statistics, and machine learning skills to real research problems. Each intern will be paired with a research mentor and participate in team discussions, present research findings, and engage with the Microsoft research community through talks and technical sessions. Research projects are designed to cover a full research lifecycle and may lead to a conference or journal publication, or contributions to a Microsoft product team.

2. Ladder University Internship Program

Location: Remote (you can work from anywhere in the world).
Cost/Stipend: Varies depending on the program; financial aid available
Acceptance rate/cohort size: Selective
Dates: Multiple cohorts throughout the year, including spring, summer, fall, and winter.
Application Deadline: Deadlines vary depending on the cohort, with options for spring (January), summer (May), fall (September), and winter (November).
Eligibility: Undergraduates and gap year students who can work for 8 - 12 weeks, devoting 10 - 20 hours/week 

The Ladder University Internship Program is a selective, virtual internship program that pairs students with startups and nonprofits worldwide. The startups span a range of industries, including software engineering, technology, and AI/ML. As part of their internship, each student will work on a real-world project that is of genuine need to the startup they are working with, and present their work at the end of their internship. Interns work closely with their manager at the startup, gaining practical experience in problem-solving and project execution. 

3. Harvard Kempner Institute Undergraduate Summer Internship Program in ML Research Engineering

Location: Kempner Institute, Harvard’s Science and Engineering Complex (SEC), Allston, MA
Cost/Stipend: Not specified
Acceptance rate/cohort size: Selective, with a limited number of available positions
Dates: June 16 - August 22
Application Deadline: Rolling until available positions are filled
Eligibility: Current undergraduates, as well as students who have earned a bachelor’s degree within the last year | must be proficient in coding (Python) and deep learning frameworks (PyTorch) 

The Harvard Kempner Institute Undergraduate Summer Internship Program in ML Research Engineering is a 10-week, fully in-person internship focused on supporting AI and machine learning research in an academic environment. You will work on a faculty-led research project and receive mentorship from members of the Kempner Institute’s Research & Engineering Team, contributing to code, models, or datasets that may be publicly released through platforms such as GitHub or Hugging Face. The work focuses on AI/ML and NeuroAI topics, including NeuroAI model optimization, LLM evaluation, distributed GPU training, and reproducible ML workflows on high-performance computing clusters. You will gain practical experience with Python, PyTorch, data engineering pipelines, and software engineering practices tailored to machine learning research. The program emphasizes hands-on engineering research rather than just theoretical study, with interns committing 35 hours per week on-site at Harvard SEC in Allston, Massachusetts.

4. Lawrence Livermore National Laboratory Data Science Summer Institute (DSSI)

Location: Lawrence Livermore National Laboratory, Livermore, CA
Cost/Stipend: Free | very competitive pay
Acceptance rate/cohort size: Around 30 students
Dates: May 18 - August 7 (Session 1) | June 22 - September 11 (Session 2)
Application Deadline: January 30
Eligibility: Students pursuing a degree in applied mathematics, computer science, computer vision, machine learning, statistics, or a similar field | must have programming skills in a high-level language such as R, Matlab, or Python, as well as experience with C/C++ and Java | must be familiar with topics such as statistical modeling and data analysis, machine learning, computer vision, multimedia signal, and more | click here for more information

The DSSI offers a 12-week, full-time, paid summer internship for advanced undergraduates and graduate students with a background in machine learning, data science, or related fields. You will split your time between a mentor-guided research project and collaborative work on a team-based data science challenge problem, applying machine learning, statistics, and high-performance computing to problems in national security, energy, health, and environmental science fields. As part of the internship, you may gain experience in areas such as computer vision, natural language processing, graph networks, predictive modeling, bioinformatics, and large-scale data mining, often using real-world datasets generated from LLNL projects. Each intern is paired with an LLNL staff scientist who will help you track your progress through regular meetings and technical guidance throughout the internship. In addition to research, you will also participate in seminars, attend short courses on topics such as deep learning and experimental design, attend facility tours, and attend networking events. The program concludes in a final presentation to laboratory leadership and peers.

5. Stanford Engineering’s Summer Undergraduate Research Fellowship (SURF) Bay Area

Location: Stanford University, Stanford, CA
Cost/Stipend: Free | $6,000
Acceptance rate/cohort size: 14 students
Dates: June 22 - August 14
Application Deadline: December 15 - February 3
Eligibility: Rising college juniors or non-graduating seniors enrolled full-time in an undergraduate degree at a non-Stanford, accredited public or private college or university in the U.S. (full-time community college students in their transfer year are also eligible to apply | must be at least 18 years old | must be in good academic standing, with a required minimum GPA of 3.0 

SURF Bay Area is a paid, 8-week, in-person summer research program at Stanford Engineering designed to give undergraduates sustained exposure to graduate-level research. You will be paired with a faculty mentor in a Stanford lab, where you work on a mentored research project involving machine learning, robotics, computer vision, or computational modeling for engineering and biomedical applications. In addition to research, the program also includes structured graduate school preparation, mentorship, networking opportunities, and cohort-based community-building activities. The program concludes with a research symposium where you present your work to the Stanford community.

6. NASA’s OSTEM Internships

Location: NASA Centers and facilities across the U.S.
Cost/Stipend: Free | paid, but the exact amount may vary based on the internship
Acceptance rate/cohort size: Selective
Dates: Internships are available throughout the year
Application Deadline: Varies depending on the internship | summer internship application deadline is February 27, and the fall deadline is May 22
Eligibility: College students who are at least 16 years old | must be U.S. citizens | required minimum GPA is 3.0 out of 4.0 | check individual internship opportunities here for project-specific prerequisites 

NASA’s OSTEM Internships offer paid, hands-on research and applied work experiences for undergraduate students at NASA centers and facilities across the country. You will work under the guidance of NASA scientists and engineers on projects involving machine learning, natural language processing, and data analysis. Internships emphasize practical skills development, with students contributing to defined projects such as analyzing aviation safety reports, working with large scientific and operational datasets, or building AI models to support space and Earth science missions. The program offers both full-time and part-time placements, depending on the role, and concludes with sharing project outcomes with peers and project teams.  

7. The Air Force Research Laboratory (AFRL) Scholars Program

Location: AFRL labs across the U.S.
Cost/Stipend: Free | stipend varies based on education level and internship location | check here
Acceptance rate/cohort size: Selective
Dates: Internships are available throughout the year, in the summer, fall, and spring semesters (exact dates vary based on the internship)
Application Deadline: Varies based on the internship | summer internship application window is from October 10 to January 10
Eligibility: Open to undergraduate students with good academic standing | minimum GPA of 3.0 out of 4.0 is highly preferred | must be U.S. citizens | must be at least 16 years old (at least 18 years old for California locations 

The AFRL Scholars Program offers paid research internships that place undergraduate students in AFRL labs where they work directly with Air Force scientists and engineers on applied research projects. You will work under the supervision of a research mentor on projects that may include machine learning, reinforcement learning for flight vehicles, automated target recognition, and physics-informed neural networks. You may gain hands-on experience in implementing and evaluating algorithms, analyzing experimental or simulation data, and integrating ML models into research workflows. Interns typically document their findings through technical reports or presentations, reinforcing research communication skills.

8. Princeton Research Experience for Undergraduate Students

Location: Princeton University, Princeton, NJ
Cost/Stipend: Free | $750/week
Acceptance rate/cohort size: Not specified
Dates: June 1 - August 3
Application Deadline: January 5 - February 15
Eligibility: Students attending a two-year or four-year accredited state or community college/university in New Jersey | must be at least 18 years old | must be U.S. citizens or permanent residents | must have completed at least 60 college credits 

The Princeton Research Experience connects undergraduate students with faculty mentors for intensive, on-campus summer research in computer science. In this program, you will work on an independent, faculty-guided research project in areas such as machine learning, natural language processing, computer vision, robotics, or computational biology. Along the way, you will gain experience with the research process, including problem formulation, experimentation, and analysis. You will be expected to engage fully with your research and deliver results over the course of the summer. The program provides a weekly stipend along with housing and a meal plan.

9. FoDOMMaT Research Experience for Undergraduates (REU)

Location: University of Illinois at Urbana-Champaign’s National Center for Supercomputing Applications (NCSA), Urbana, IL
Cost/Stipend: Free | $700/week plus housing, meal plan, and one round trip to and from campus
Acceptance rate/cohort size: 10 students
Dates: May 27 - July 31
Application Deadline: January 20 - March 25
Eligibility: Undergraduate students with good academic standing | must be at least 18 years old | must be U.S. citizens or permanent residents | Python, along with some experience with software development, is required | must have some exposure to machine learning via coursework, self-study, or other projects

The FoDOMMaT (The Future of Discovery: Training Students to Build and Apply Open Source Machine Learning Models and Tools) is a 10-week, on-site summer REU at the University of Illinois Urbana-Champaign’s NCSA focused on building and applying open-source machine learning tools for scientific research. You will begin with a week of structured training in machine learning and deep learning methods, then spend nine weeks working on a mentored research project with guidance from both a domain expert and an ML specialist. Projects span across applied ML areas such as geospatial and climate modeling, generative AI for materials science discovery, computer vision and large language models for nutrition and dietary recommendations, and AI for medical imaging. Interns develop practical skills in Python-based ML frameworks, data preprocessing, model training, and open-source software development using high-performance computing resources. The program emphasizes open science, requiring you to document and share code and models. The experience also includes seminars, professional development events, and regular mentor meetings. The program concludes with a written report and oral presentation at an undergraduate research symposium conducted on campus. 

10. Amazon Internships

Location: Multiple sites across the U.S. and the world
Cost/Stipend: Free | compensation may vary based on geographical location, education level, experience, and skills
Acceptance rate/cohort size: Selective
Dates: Internship opportunities are available year-round
Application Deadline: Rolling; varies depending on the internship
Eligibility: Open to undergraduates who are rising seniors or recent graduates

As an Amazon intern, you may work full-time with a research or product team focused on artificial intelligence, machine learning, or robotics, depending on the role and placement. You may contribute to projects at the intersection of large language models, generative AI, reinforcement learning, computer vision, and robotic perception and control, applying these concepts to real-world systems. Interns are expected to take full ownership of their projects, from problem formulation and experimentation to implementation and evaluation. You will work under the guidance of a manager and an assigned mentor, and collaborate with scientists, engineers, and cross-functional teams throughout the internship. You may also participate in hands-on research using modern ML frameworks, such as PyTorch or JAX, and production-scale data and infrastructure. Internships are conducted full-time, typically require relocation to the host site, and are open to current undergraduate students who can commit to the entire duration.

11. Brown Computer Science’s "Artificial Intelligence for Computational Creativity" REU

Location: Brown University, Providence, RI
Cost/Stipend: Free | $6,300
Acceptance rate/cohort size: 8 students
Dates: June 1 - July 31
Application Deadline: February 3
Eligibility: Open to undergraduate students, as well as graduating high school students who have been accepted into an undergraduate program but have not yet started (students who have received their bachelor's degrees and are no longer enrolled as undergraduates cannot apply) | must have at least completed an introductory computer science course sequence as well as mathematics courses covering calculus, linear algebra, and probability 

The Brown Computer Science’s Artificial Intelligence for Computational Creativity REU is a 9-week, fully funded, residential summer research program hosted on Brown University’s campus. You will work on an original, faculty-mentored research project focused on creative applications involving AI, with possible focus areas including generative models for text or images, detecting fake content, AI for game playing, and user experience design for creative AI systems. Each participant is paired with both a faculty mentor and a graduate student mentor and participates in weekly study groups that help them develop and present a research proposal. The program is conducted in partnership with the Leadership Alliance, which provides structured career development activities, graduate school preparation, and professional networking opportunities. You will also participate in social and cultural activities, including local site visits and community events. The program provides a stipend along with housing and travel support, allowing you to focus full-time on research and related activities.

12. University of North Texas (UNT)’s "Beyond Language: Training to Create and Share Vector Embeddings across Applications" REU

Location: University of North Texas, Denton, TX
Cost/Stipend: Free | $7,000 (taxable) | housing, travel, and meals are also covered
Acceptance rate/cohort size: 10 students
Dates: May 19 - July 25
Application Deadline: March 21
Eligibility: Rising undergraduate sophomores, juniors, and seniors with strong academic standing | must be U.S. citizens or permanent residents

The UNT’s "Beyond Language: Training to Create and Share Vector Embeddings across Applications" REU is a 10-week, NSF-funded summer research program focused on teaching undergraduates how modern AI systems use vector embeddings to represent and transfer knowledge. You will work with UNT faculty and graduate mentors on a defined research project, learning how to build, evaluate, and document embedding-based machine learning models across domains such as healthcare, climate science, finance, recommender systems, materials science, and biology. The program is structured in such a way that the first half of the program emphasizes training in embedding strategies and applied machine learning. In contrast, the second half of the program focuses on individual research projects, along with guided troubleshooting and experimentation. You may contribute to authentic research tasks such as evaluating large language models, creating visualizations, and producing reproducible analyses. Participants will also have the chance to collaborate with the broader interdisciplinary AI summer research community at UNT, working alongside both UNT students and external REU peers. 

13. Illinois Tech’s Summer Undergraduate Research Experience (SURE)

Location: Illinois Institute of Technology, Chicago, IL
Cost/Stipend: Free | $550/week plus free housing
Acceptance rate/cohort size: Not specified
Dates: June 2 - August 8
Application Deadline: January 31
Eligibility: Undergraduate students with a foundational background in mathematics, including calculus, differential equations, linear algebra, and some programming skills | must be U.S. citizens or permanent residents

Illinois Tech’s SURE program is a 10-week NSF-funded summer experience that introduces students to research in data science, machine learning, and computational mathematics. You will work on mentored research projects involving topics such as machine learning for spatial-temporal data, AI-based safety analytics, or accelerated simulation methods, applying mathematical and statistical concepts to real-world problems. The program combines hands-on research with guidance from faculty and graduate mentors, emphasizing model development, data analysis, and computational experimentation using tools such as Python. You will collaborate as part of a research team, gaining experience in technical problem-solving, the academic research process, and scientific communication. Additional activities include professional development workshops and mentorship sessions that provide insight into academic and career pathways.

14. Rutgers WINLAB Summer Internship Program

Location: WINLAB, Rutgers University, North Brunswick Township, NJ
Cost/Stipend: Free | both paid and unpaid internships are available
Acceptance rate/cohort size: 15 - 20 undergraduate students
Dates: May 27 - August 7
Application Deadline: April 6
Eligibility: Students currently enrolled full-time in a college or university who will be graduating the year after their internship or later | must be eligible to work in the U.S. | check individual research project descriptions here for project-specific prerequisites 

The Rutgers WINLAB Summer Internship Program places students in faculty-led research groups focused on wireless systems and machine learning applications. You may work on projects such as applying ML to 5G and satellite network coexistence, edge-based AI for AR/VR and autonomous vehicles, and decentralized learning over wireless networks. You may participate in activities such as building and testing models in Python and PyTorch, analyzing network and sensor data, and developing software for real-time and low-latency systems. The program includes weekly progress meetings, close mentorship from graduate students and faculty, and collaborative, team-based research. At the end of the internship, you will also be required to submit a written report and deliver a formal presentation showcasing your results.

15. Allen Institute for Artificial Intelligence (Ai2) Internships

Location: Allen Institute for Artificial Intelligence (Ai2), Seattle, WA
Cost/Stipend: Free | pay is competitive and varies based on position and education level
Acceptance rate/cohort size: Not specified
Dates: Internships are 12 weeks long and available year-round
Application Deadline: Varies depending on the internship | summer internships application deadline is January 4

Eligibility: Open to undergraduate students; check individual internship opportunities here for internship-specific prerequisites 

The Ai2 Internship Program places undergraduates in research and engineering roles focused on applied artificial intelligence. As an intern, you will work on projects in areas such as natural language processing, machine learning, AI systems, and open science tools. You will gain experience developing experimental platforms, implementing published models into AI demos, and contributing to research workflows that support projects. You will be paired with a mentor who guides your technical development and helps structure your contributions to ongoing research and engineering efforts. The internship is best suited for students interested in gaining experience in AI research practices, software development for AI systems, and collaborative work in a professional environment. You may also have the chance to co-author papers or contribute to conferences and journals.

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