15 Machine Learning Internships for Undergraduates
Internships are one of the most effective ways for college students to gain work experience while still in school. They provide exposure to professional workflows, industry tools, and collaborative environments. Through internships, you build technical and soft skills, gain clarity about your career direction, and develop valuable connections with mentors and peers. Just as importantly, internships are a strong addition to your resume, signaling initiative and competence to future employers or graduate programs. Online internships, in particular, are accessible options. For students interested in machine learning, internships offer direct exposure to data pipelines, model development, experimentation, and deployment in professional settings.
Why should I do a machine learning internship in college?
A machine learning internship allows you to apply theoretical concepts, like supervised learning, neural networks, and model optimization, to datasets and business or research problems. You gain experience working with production-level code, version control systems, and cross-functional teams. They help you understand how machine learning solutions are built, tested, and deployed at scale. Internships also create opportunities to network with engineers, data scientists, startup founders, and researchers who can offer mentorship, references, or even job opportunities. Many students receive return offers or strong recommendation letters after performing well in internship roles, significantly boosting their employment chances after graduation.
In this guide, we’ve narrowed down our list of 15 top machine learning internships for undergraduates using criteria such as prestige, rigor of professional experience, and opportunities to network with industry leaders and research mentors.
1. Ladder University Internship Program
Location: Remote
Cost/Stipend: Varies depending on the program type; financial aid available / No stipend
Acceptance rate/cohort size/cohort size: 10–25%; 70–100 students per session
Dates: Multiple cohorts throughout the year, including Spring, Summer, Fall, and Winter.
Application Deadline: Varies 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. Apply now!
2. Microsoft Research – Undergraduate Research Internship (Computing)
Location: Redmond, WA; New York City, NY; New England, US
Stipend: Paid, amount not disclosed
Acceptance rate/cohort size: Highly selective; small cohorts
Dates: 12 weeks (Summer; typically May–August)
Application Deadline: Early January
Eligibility: Rising juniors or seniors in CS, CE, Software Engineering, Information Science, or related majors; 2+ years of programming and completion of Calculus and Probability/ML coursework
This 12-week summer internship places advanced undergraduate students in Microsoft Research labs across the U.S. You will conduct research in areas such as artificial intelligence, computer vision, systems, security, HCI, and machine learning. You are paired with mentors and collaborate with doctoral interns, faculty visitors, and research scientists. The program emphasizes research publication, technical presentations, and exposure to graduate-level research pathways. It also encourages diversity in computing and provides strong community-building and networking support. Many participants pursue advanced degrees following the internship.
3. Rivian – Artificial Intelligence, Machine Learning & Data Science Summer Internship
Location: Palo Alto & Irvine, CA (also Normal, IL & Plymouth, MI)
Stipend: Varies as per location between $25 – $51/hour
Acceptance rate/cohort size/cohort size: Highly competitive
Dates: 12-16 weeks (Summer)
Application Deadline: Rolling basis
Eligibility: Students pursuing a Bachelor's, Master's, or PhD in CS, AI, ML, Data Science, or related field (Graduating Fall to Spring after 2 years)
In this internship, you will learn about artificial intelligence, data science, and autonomous driving for electric vehicles. You will work on real projects, write code in Python or C++, troubleshoot data issues, and build machine learning models using tools like TensorFlow or PyTorch. You get to help create technology for electric adventure cars while working with expert mentors in the automotive industry. By the end of the summer, you will learn how to build smart computer models, solve complex data problems, and write better software for self-driving cars.
4. NVIDIA – Deep Learning Internships
Location: Santa Clara, CA (and other US locations depending on team)
Cost: $20–$71/hour, depending on experience and level
Acceptance rate/cohort size: Highly competitive; 1,000+ interns globally
Dates: 12 weeks (Summer); year-round options available for 3–6 months
Application Deadline: Rolling applications
Eligibility: Students pursuing Bachelor’s, Master’s, or PhD students in EE, CE, CS, or related fields
NVIDIA’s Deep Learning Internships provide a highly coveted and technical internship, involving hands-on experience with GPU-accelerated machine learning systems. You will work on deep learning applications, frameworks, and high-performance computing optimization, contributing to libraries such as cuDNN and CUDA. Projects range from algorithm development to large-scale distributed training and performance tuning. The internship emphasizes real-world production impact and exposure to industry-leading AI hardware. You gain experience optimizing neural networks for computational efficiency and scalability, making it particularly attractive for ML systems and infrastructure enthusiasts.
5. Lenovo – AI Intern Engineer
Location: Chicago, IL (On-site)
Stipend: $33 - $44 per hour
Acceptance rate/cohort size/cohort size: Highly selective; cohort size not specified
Dates: Six-month duration starting in the summer
Application Deadline: Rolling (accepted until the position is filled)
Eligibility: Undergraduate seniors in Computer Science or a related technical field, attending a US degree program, with programming experience
This six-month internship at Lenovo gives you the chance to work with engineering teams to build artificial intelligence into future technology products. You will cover important topics like natural language understanding, machine learning, deep learning, and software engineering. During the program, you will design prototype applications, create predictive models, clean large datasets, and shadow experienced engineers. A unique feature of this role is its flexible and open-ended setup, which allows you to explore creative projects across different departments. This means you will interact directly with product development, customer experience, and strategy teams.
6. Apple – AIML Internship (Artificial Intelligence & Machine Learning)
Location: Cupertino, CA; Seattle, WA; Austin, TX (varies by team)
Cost: Paid internship
Acceptance rate/cohort size: Highly selective; cohort size not publicly disclosed
Dates: 12 weeks (Summer; May–August typically); Co-ops: May occur during the academic year for 3–6 months
Application Deadline: Rolling basis
Eligibility: Undergraduate, Master’s, or PhD students in CS, EE, Data Science, or related disciplines; returning to school to continue education, or the internship is the last requirement for graduation
Apple’s Artificial Intelligence and Machine Learning internships place students within specialized AI and machine learning teams across hardware, software, Siri, vision, and on-device intelligence. You will work on applied ML projects such as deep learning model development, privacy-preserving AI, and system optimization. The experience emphasizes product-oriented research, meaning interns see how ML models integrate directly into consumer devices. Mentorship from senior engineers and researchers supports both technical depth and professional growth. This program is ideal for students interested in real-world AI deployment at scale.
7. Tesla – AI & Autopilot Internship
Location: Palo Alto, CA; Austin, TX
Stipend: $100,000 - $150,000 + benefits (prorated for the internship’s duration)
Acceptance rate/cohort size: Highly selective; total annual intern count is ~2,500–3,000
Dates: 12–16 weeks (Summer; some fall/spring options)
Application Deadline: Rolling applications
Eligibility: Undergraduate and graduate students in CS, Robotics, EE, AI, or related fields
Tesla’s AI & Autopilot internships focus on real-world computer vision, neural networks, and robotics applications. You will work on full self-driving (FSD) systems, perception stacks, or large-scale video dataset training. Projects often involve high-performance model deployment and algorithm optimization. The environment is fast-paced and product-driven, offering exposure to AI in autonomous systems. You contribute directly to production-grade AI systems used in millions of vehicles. Tesla's AI and Autopilot internships are among the most prestigious and demanding undergraduate opportunities in the world. They operate on a "High Impact" philosophy, treating interns as full-time engineers.
8. NASA Jet Propulsion Laboratory – Machine Learning & AI Internships
Location: Pasadena, CA
Stipend: Paid, amount not publicly disclosed
Acceptance rate/cohort size: Highly selective; roughly 500–1,000 interns
Dates: 10–12 weeks in the Summer (Spring and Fall options available)
Application Deadline: Typically, March
Eligibility: Undergraduate and graduate students in STEM fields; U.S. citizens or legal permanent residents; minimum 3.0 GPA
Machine Learning and AI internships at NASA Jet Propulsion Laboratory (JPL) for undergraduates are highly coveted positions that place students in the heart of robotic space exploration. They involve the application of machine learning to planetary science, space exploration, robotics, and astrophysics research. You will collaborate with scientists and engineers on problems such as spacecraft autonomy, data analysis from telescopes, and anomaly detection in mission data. The program blends advanced AI research with real aerospace applications. Students gain exposure to mission-driven research environments and contribute to projects supporting NASA’s space exploration goals.
9. Hyundai Motor Company (HATCI) – ADAS Machine Learning Engineering Intern
Location: Superior Charter Township, MI (Hybrid)
Stipend: Paid hourly, rate not disclosed
Acceptance rate/cohort size/cohort size: Competitive; cohort size not disclosed
Dates: Summer (June – August)
Application Deadline: Early to Mid-April
Eligibility: Currently pursuing a full-time undergraduate engineering degree (CS, ML, computer vision, data science); legally authorized to work in the U.S.; proficiency in Python or C++
This internship plunges you into the core of autonomous driving software development, focusing heavily on large-scale data processing for deep neural network perception models. You will explore critical automotive AI topics like computer vision, object detection, end-to-end driving models, and multi-modal sensor analysis. Over the summer, you will annotate images to train datasets, apply unsupervised clustering to identify data anomalies, build automated data ingestion tools, and support physical test vehicle instrumentation. A unique feature of this program is the direct exposure to real-world, in-vehicle hardware, allowing you to log and utilize raw data from cameras, radars, IMUs, and LiDAR.
10. Upstart – Machine Learning Research Internship
Location: Remote (United States or Canada, excluding Quebec) – with periodic team on-sites in cities such as San Mateo, CA; Austin, TX; Columbus, OH; or New York City
Stipend: $141,000 – $150,000 (prorated as per internship’s duration)
Acceptance rate/cohort size: Highly selective; typically ~15–20 interns across ML/DS
Dates: Standard 10–12 week duration, typically starting in June
Application Deadline: March 9
Eligibility: Undergraduate or master’s students in computer science, physics, machine learning, or related quantitative fields; on track to graduate by next Summer; strong Python skills and foundations in probability, statistics, and machine learning required.
The Machine Learning Engineer Internship at Upstart offers undergraduates hands-on experience building production-grade machine learning systems in a real-world fintech environment. You work alongside research scientists and ML engineers to improve model performance, efficiency, and deployment pipelines. Projects may include optimizing algorithms, designing data pipelines, and automating workflows that bridge research and production systems. The internship emphasizes scalable engineering practices, statistical rigor, and collaboration across stakeholders. This role is ideal for students interested in applied machine learning, AI systems, and high-impact product-driven modeling in industry.
11. Kempner Institute at Harvard University – Undergraduate Summer Internship in ML Research Engineering
Location: Allston, MA (Harvard Science and Engineering Complex)
Stipend: Paid, amount not disclosed
Acceptance rate/cohort size: Highly selective; small cohorts
Dates: June 15 – August 21
Application Deadline: March 30
Eligibility: Current undergraduates eligible to work in the U.S.; proficiency in Python and PyTorch is required
The Kempner Institute’s 10-week summer internship offers immersive ML research engineering experience within an academic AI lab. You will be mentored by the Research & Engineering Team and work on faculty-directed projects in areas like LLMs, distributed GPU training, NeuroAI, model optimization, and scalable AI workflows. You contribute to open-source tools, datasets, and AI models that may be publicly released on GitHub or Hugging Face. The program emphasizes high-performance computing, reproducibility, and applied research engineering best practices. This opportunity is especially suited for students interested in the engineering backbone of frontier AI research.
12. Princeton University – Research Experience for Undergraduates (REU), Computer Science
Location: Princeton, NJ (residential, on campus)
Stipend: $750/week
Acceptance rate/cohort size: Highly selective; typically 8–12 students
Dates: June 1 – August 2
Application Deadline: February 15
Eligibility: U.S. citizens or permanent residents; 18+; college students with at least 60 credits; cannot graduate before August; current Princeton students not eligible
Princeton’s CS REU provides undergraduates with faculty-mentored research experience in computer science. You will conduct research alongside Princeton faculty, gaining exposure to the research process, from problem formulation to experimentation and presentation. The program aims to broaden participation in CS research and create inclusive pathways into advanced study. You present your work at the end of the program and build strong academic mentorship connections. With full funding and an immersive campus experience, this REU is particularly valuable for students considering graduate school in computer science or AI-related fields.
13. TikTok – Machine Learning Engineer Intern (USDS)
Location: San Jose, CA (Hybrid: 3 days/week in-office)
Stipend: Paid, amount not disclosed
Acceptance rate/cohort size/cohort size: Highly competitive; cohort size not explicitly stated
Dates: 12 weeks during Summer (Multiple start dates offered across May and June)
Application Deadline: Rolling basis
Eligibility: Currently pursuing a BS/MS in Computer Science, Engineering, Math, Economics, Statistics, or a related discipline; graduating December or later; coding experience in Java, Go, or Python
In this 12-week hybrid internship, you will immerse yourself in the intersection of machine learning and data security within TikTok's US Data Security (USDS) team. You will cover critical AI topics, including clustering, graph mining, sequence modeling, and large language models. Throughout the summer, you will build machine learning models, analyze attack patterns to mitigate risks, develop robust data mining tools, and construct recall models for recommendation systems. A uniquely defining feature of this program is its strict mandate to improve user experience while operating under rigorous national data compliance and privacy safeguards.
14. Amazon Web Services – AI & ML Scholars
Location: Virtual (Global)
Cost/Stipend: No cost / AWS covers the 4-month Udacity Nanodegree cost
Acceptance rate/cohort size: Highly selective for Nanodegree Phase; 2,500 students annually
Dates: May – November (Challenge Phase: May – August; Nanodegree: August 25 – November 25)
Application Deadline: August 1
Eligibility: Students 18+ worldwide; no prior AI/ML experience required
AWS AI & ML Scholars is a two-phase program designed to build foundational and applied AI skills. You begin in the Challenge Phase, learning generative AI fundamentals and building applications using AWS tools like PartyRock. Selected participants advance to a fully funded 4-month Udacity Nanodegree in tracks such as AI Engineer or AI Scientist. The curriculum includes real-world projects using Amazon generative AI services. The program is beginner-friendly, global, and career-oriented, making it accessible to students transitioning into AI from diverse academic backgrounds. It blends structured coursework with applied project experience.
15. Stanford Artificial Intelligence Laboratory – Undergraduate Research Opportunities
Location: Stanford University, Stanford, CA
Stipend: Paid, amount not disclosed
Acceptance rate/cohort size: Highly selective; typically 80–120 students across CS
Dates: 10 weeks between June and August
Application Deadline: February 10
Eligibility: Stanford Undergraduates only; must maintain undergraduate status through the summer
Stanford AI Lab (SAIL), primarily facilitated through the CURIS (Computer Science Undergraduate Research Internship) program, offers undergraduate research opportunities across robotics, NLP, computer vision, AI ethics, and systems. You typically join through direct faculty outreach or structured research programs. Work often contributes to leading AI conferences such as NeurIPS, ICML, or CVPR, where you gain exposure to cutting-edge AI research in one of the world’s most prestigious academic AI environments. The experience is well-suited for students considering graduate school or long-term research careers.
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