AI Internships: Areas to Explore and How to Find One

Key takeaways

Whether you're a computer science student eager to shape the future of self-driving cars or a data science student interested in improving the quality of a chatbot's responses, an artificial intelligence (AI) internship can provide you with an opportunity to contribute to this emerging technology.

• Many AI companies hire interns as a way to recruit talent early, draw from students' unique academic knowledge, and fulfill practical business needs.

• There are different AI areas to intern in, such as machine learning, data science, and AI ethics.

• Qualifying for an internship typically means being an upper-level undergraduate or graduate student, and having relevant technical skills, such as programming and an understanding of ML frameworks.

Discover the different types of AI internships available to explore, what you'll need to qualify, and how to find relevant opportunities. Afterward, consider advancing your AI development knowledge with Vanderbilt University's AI Agent Developer Specialization.

What types of AI internships are available?

AI internships are typically available in various specializations, such as machine learning, natural language processing (NLP), computer vision, data science, and more. Not every AI company will offer an internship in each of these areas, so if you're particularly set on one, research relevant companies doing work specifically in that area.

1. Machine learning internships

In a machine learning internship, you’ll typically work alongside experienced engineers, potentially experiencing everything from algorithm development to data analysis. Under the guidance of a mentor, you might find yourself debugging code, fine-tuning machine learning models, or exploring the mathematical foundations of AI. 

2. Natural language processing internships

An natural language processing (NLP) internship can be your first step toward becoming an NLP engineer, where you'll create systems that help machines understand and process human language. As an intern, you'll likely use machine learning combined with practical problem-solving to gain experience designing and building AI models that can analyze text, recognize speech patterns, and generate natural language while constantly fine-tuning their performance. 

3. Computer vision internships

Professionals in the field of computer vision train machines to understand the visual world. As an intern, you may have the opportunity to work with various industry-standard tools, such as OpenCV, TensorFlow, and PyTorch, to develop systems that can detect objects in real-time and process visual data intelligently. From building facial recognition systems to creating augmented reality experiences, an internship in computer vision can offer you various opportunities.

4. Data science internships

As a data science intern, you'll work alongside experienced practitioners to collect, analyze, and interpret data that drives product development. You might have responsibilities such as assisting in creating custom models and algorithms to extract insights from complex data sets or collaborating with cross-functional teams to implement solutions and measure their impact. Your experience as a data science intern may also include learning to program, build models, and create visualizations.

5. Robotics internships

A robotics internship can be your first step toward becoming a robotics engineer or autonomous systems developer, where you'll create intelligent machines that can perceive, navigate, and interact with the physical world. As an intern, you'll likely combine AI algorithms with hardware integration to gain experience programming robotic systems, implementing computer vision for navigation, and developing control systems that enable robots to perform complex tasks while continuously learning from their environment.

6. AI ethics and safety internships

An AI ethics internship can be your first step toward becoming an AI policy researcher, ethics consultant, or responsible AI specialist, where you'll ensure AI systems are developed and deployed responsibly. As an intern, you'll likely use critical analysis combined with technical understanding to gain experience auditing AI models for bias, developing fairness metrics, and creating governance frameworks that help organizations build trustworthy AI while balancing innovation with societal impact.

7. AI product management internships

An AI product management internship can be your first step toward becoming an AI product manager or technical product lead, where you'll bridge the gap between AI capabilities and market needs. As an intern, you'll likely use business analysis combined with technical knowledge to gain experience defining product requirements, collaborating with engineering teams on AI feature development, and analyzing user data to guide product strategy while translating complex AI concepts into valuable customer solutions.

What does an AI intern do?

As an AI intern, you'll likely have the opportunity to participate in hands-on AI development work that can help you build practical skills while also allowing you to contribute to meaningful projects. Consider the following examples of types of work you might experience:

• AI model development: This work can include building and fine-tuning AI models using data preprocessing and cleaning to boost model performance and working hands-on with supervised, unsupervised, and reinforcement learning techniques.

• Research and model analysis: As an intern in this area, you might analyze large data sets to uncover insights that guide AI development, test AI models to ensure they're performing as intended, identify and resolve issues that arise, and provide information on emerging AI trends and best practices. 

• Documentation and technical communication: Maintaining detailed records of AI experiments and development processes will likely be one of your responsibilities as an intern in this area. Additionally, you may help create reports and presentations that communicate findings and AI research outcomes.

• Project collaboration: Interns typically work with various people, including researchers, engineers, and program managers, to develop innovative solutions. 

• Technical growth: An internship can be a great time to gain hands-on experience with industry-standard tools, such as TensorFlow, PyTorch, and Scikit-learn. The opportunity to use these tools in real-life situations can help to accelerate your technical development. 

Beyond your core responsibilities as an AI intern, you may also tackle real-world challenges that make a tangible difference. You might develop specialized chatbots that transform how companies interact with customers, create AI systems that revolutionize how people find career opportunities, or build tools that help children with learning challenges. From health care simulations to interactive AI assistants, you'll likely work on diverse projects that push the boundaries of what's possible while learning from experienced mentors who'll help you grow from beginner to contributor.

What are the requirements for an AI internship?

AI internship requirements will differ by company. Here are some general requirements for AI internships:

Educational background

AI companies look for junior or senior undergraduates or graduates in relevant fields. They may prefer degree candidates from computer science, data science, mathematics, statistics, electrical engineering, or related technical fields.

Technical skills

Internships are an opportunity to apply skills you're developing. Some skills a company may want candidates to have include:

• Programming languages: Python, R, Java, C++, or JavaScript

• ML frameworks: Experience with TensorFlow, PyTorch, scikit-learn, or similar libraries

• Data manipulation: Pandas, NumPy, SQL for data analysis and preprocessing

• Version control: Git/GitHub proficiency for collaborative development

Soft skills

In addition to technical skills, AI companies may want to see that you've developed the following professional skills:

• Problem-solving: Analytical thinking and ability to break down complex problems

• Communication: Ability to explain technical concepts clearly

• Curiosity: Demonstrated passion for AI

• Collaboration: Experience working in teams or contributing to group projects

Practical experience

As an undergraduate or graduate student, you may still need to show a projects portfolio of your academic or personal work that demonstrates key AI skills. You may also need to show that you've completed relevant coursework or participated in hackathons or open source repositories.

How do I get an AI internship?

Securing an internship will involve finding relevant openings, tailoring your materials, and applying. Explore some tips on finding your internship and completing the application process.

Finding an AI internship

A variety of options exist for finding an AI internship. As you look for an internship, consider the following options: 

• Job boards and websites: Many platforms feature detailed listings and direct application links for various internship opportunities in areas from development to design. These sites can help you match your skills with relevant positions in machine learning, data science, and natural language processing. 

• Company websites: Major tech companies also run structured internship programs that immerse you in cutting-edge AI projects. Google, for instance, has a permanent part of its website dedicated to internship information.OpenAI also offers a direct path to employment, with its six-month program geared toward researchers and engineers. 

• Academic institutions: University career services can connect you to valuable AI internship opportunities through research programs and industry partnerships. Research programs also provide additional pathways and resources.

Application process and networking opportunities

Breaking into AI begins with strategic internship applications and building strong industry connections. Successful candidates typically follow three key steps:

• Tailor your materials: When crafting your AI resume, highlight your technical competencies and provide concrete examples of how you've applied them. Lead with a powerful summary that includes your relevant AI skills and achievements. Use specific metrics and outcomes to demonstrate impact. Include actionable expertise and showcase projects, code samples, and technical documentation by linking to a digital portfolio. 

• Ace the interviews: Prepare for your AI internship interviews by researching the company's AI initiatives and projects to show your interest. Practice explaining complex AI concepts in simple terms, as interviewers often want to see your ability to communicate technical ideas. Prepare concrete examples of your AI projects, focusing on technical implementation, the problem-solving process, and lessons learned. When answering technical questions, think aloud and walk through your reasoning step-by-step—interviewers often care more about your thought process than perfect answers. 

• Connect with the AI community: Build meaningful connections in the AI community through active engagement. Consider joining local AI meetups and conferences. Complement this with an online presence—participate in AI discussions on platforms to collaborate on real projects and showcase your work. You may also want to follow AI leaders on social media to engage thoughtfully with their content and share your insights and projects.

Internship duration and compensation

AI internships offer flexible paths to real-world experience. As you decide if an internship is the right choice for you, you may want to consider the following details regarding duration and compensation: 

• Duration: Internship seekers have options ranging from 10 to 12 weeks for summer programs to 3 to 12 months for year-round programs. Many positions require a 40-hour weekly commitment, though some companies offer part-time roles. 

• Paid vs. unpaid: While $19 to $21 per hour [1] is the average pay for entry-level positions, you may earn a higher wage depending on your location [2]. 

Benefits of AI internships

An AI internship offers several short-term and long-term benefits. These can include:  

• Higher salary and increased job opportunities: AI internships provide valuable hands-on experience with real-world projects and measurable impact. Research from StandOut CV indicates that 66.4 percent of interns secure full-time positions, commanding salaries approximately $15,000 higher than their non-intern counterparts [3].

• Portfolio building: The time and effort you invest in an AI internship can help you build an employer-ready AI portfolio. 94 percent of hiring managers prioritize graduates with internship experience [4]. 

• Networking opportunities: AI internships provide valuable opportunities to connect with industry professionals who can share insights into tech trends and career paths. Beyond the immediate experience, these relationships can lead to job offers and referrals, evolve into mentorship relationships, and help you develop your professional brand.

Strengthen your AI skills on Coursera

Keep your finger on the pulse of AI with our LinkedIn newsletter Career Chat. Or, check out the following digital resources to keep expanding your AI knowledge: 

• Watch on YouTube: How Does GenAI Work? or 5 Fun Facts About GenAI 

• Hear from a faculty expert: AI Creativity Unleashed: Expert Insights from Vanderbilt’s Dr. Jules White

• Learn whether an AI career is right for you: Take our AI career quiz

Whether you want to develop a new skill, get comfortable with an in-demand technology, or advance your abilities, keep growing with a Coursera Plus subscription. You’ll get access to over 10,000 flexible courses from over 350 top universities and companies.

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