How to Land a Machine Learning Internship: A 2025 Career Guide

Machine learning lies at the heart of many of the goods and services we use every day, from the search engines we rely on for research at school and work to the video streaming platforms we relax with at night. As machine learning models become more and more important to businesses around the world, the demand for machine learning professionals to train, design, and deploy them rises alongside it. 

In India, the machine learning and artificial intelligence market is projected to reach 17.87 billion USD by 2030 due to a compounded annual growth rate of 36.11 per cent per year [1]. Taking part in a machine learning internship can help you gain practical experience and witness first-hand the way this explosive market growth is changing industries. Explore what a machine learning internship is, the skills you’ll need to enter one, and tips for how to begin your search process. 

Overview of machine learning internships

A machine learning internship can help you lay the groundwork for future professional success. Not only can you build in-demand skills that stand out to future employers, but you can try out different areas and build your professional network.

What does a machine learning intern do?

The duties and responsibilities you’ll perform as a machine learning intern will vary from one internship to another. As an intern, you might work with different data formats, use programming languages for data manipulation, and generally prepare data for more advanced models. You might also be involved with designing and implementing machine learning models in cloud-based environments, adapting and developing ML algorithms for business purposes, or supporting development or engineering teams throughout the project lifecycle. Depending on your organisation and team, you might also have the opportunity to gain experience with quality assurance pipelines, troubleshooting, conducting integration tests, and working cross-functionally across departments. 

If you have a specific skill you’d like to develop or an area you are interested in, you should look for internships that advertise that particular area to ensure you are finding the right fit.

Skills for landing a machine learning internship

Whether you’re an aspiring data scientist or an AI engineer hoping to one day work on computer vision, the skills you’ll hone in a machine learning internship can help set you up for future professional success.

Machine learning has many applications, but some of the foundational skills tend to remain similar across areas. Building relevant skills for machine learning applications before entering your internship can ensure you are prepared for the real-world applications you are likely to encounter on the job. A few technical and people skills that might help you stand out when searching for an internship include: 

• Knowledge of programming languages such as R, Python, Java, or C/C++

• Understanding of data structures, algorithms and computer architectures

• Experience with data modelling and applied mathematics

• Experience building models with deep learning frameworks like Tensorflow 

• Experience deploying models with Flask, Django, AWS, Azure, or other cloud services

• Knowledge of relevant statistical, mathematical, and computational concepts

• Ability to collaborate with others and work on a team

• Strong written and verbal communication skills

• Curious disposition that allows you to think both critically and outside the box

• Interest in learning the latest technologies and methods in this space

Benefits of a machine learning internship

In addition to having a related job title that you can add to your resume, you’ll gain real-world work experience, professional networking opportunities, and the chance to hone important workplace skills like collaboration and communication. 

Internships supplement the training you have received in school with real-world work experience that gives you an idea of what your professional future may look like. 

How to find a machine learning internship 

You can find a machine learning internship in many different ways, including job posting sites, company pages, and through leveraging your professional and personal network. When searching for an internship, taking advantage of all available opportunities may help you find the most opportunities. 

1. Search job posting sites

To find a machine learning internship on a job posting site, go to your site of choice and simply search for “machine learning internship.” From there, you can view a list of currently available internships.

Some popular websites to search for internships include: 

• Internshala

• LinkedIn

• Indeed

• Glassdoor

• Naukri.com

2. Explore a company's careers page.

To find an internship on a business’ dedicated job page, go to a search engine, such as Google, and simply search “[business’ name] jobs.” Once on the dedicated job page, search for “machine learning internship” and see if any are available. You might also consider searching for a related position, such as “machine learning engineer internship” or “data science internship.”

In some cases, you might have more luck going to smaller, lesser-known companies that receive a lower volume of applications. However, if you want to apply to leaders in the industry, connecting with professionals at the company who have a connection to your university or current professional network can help facilitate an introduction or help your application stand out.

3. Connect with your network.

Joining interest groups, going to organised workshops or conferences, connecting with people in your field online, and joining online communities can help you build connections with established people in the industry who may be aware of opportunities that fit your interests. Not only can this connect you to opportunities, but it can help your application gain name recognition during the hiring process. 

What qualifications do you need for a machine learning internship? 

The requirements for a machine learning internship vary greatly from one to another. However, most internships will likely require that you have some understanding of programming languages like Python or R, working with ML algorithms and training ML models, and are comfortable working with various types of data. 

While the internship might not require a specific set of experiences, in some cases, hiring personnel may look for candidates who have demonstrated experience and knowledge in the required skills. This might be through a university, certificate course, or through a portfolio of competitive projects. In general, participating in competitions, boot camps, and open-source projects can help you showcase your expertise. From here, building a resume that highlights relevant coursework and experiences is important to create an accurate image of your knowledge and skills. 

Tips for applying to a machine learning internship

It’s always important to make the best first impression when applying for an internship. To help you do just that, here are some key things you should keep in mind throughout the process:

Apply ahead of time. 

Many internships start looking for candidates well before the start date, so make sure to apply well in advance. Many summer internships, for example, start looking for applicants as early as spring or early winter. 

Know the type of internship you want.

You can find different types of machine learning internships depending on your availability and preference. Some internships may be paid, while others may be on a volunteer basis. You will also find differences in hours (full-time, part-time, project-based) and location (in-person, online, hybrid), so it’s important to think carefully about what your priorities are.

Apply to multiple internships. 

Machine learning internships can be highly competitive, so it’s wise to apply to many different ones to increase your chances of being accepted. 

Use a portfolio. 

One of the best ways to highlight your skills is through a portfolio that showcases related machine learning projects you’ve done in the past.

Use your personal network to find opportunities. 

One of the most valuable resources for finding a suitable internship is your existing network of peers, mentors, and professional contacts. Ask for recommendation letters early. 

In some cases, you might have the opportunity to provide a letter of recommendation when applying, so it’s important to source those recommendations early enough in the process to meet the application deadline. 

Tailor your resume and cover letter. 

Make sure to tailor both your resume and cover letter to each internship and to proofread all your materials before submitting them. 

Prepare for a machine learning internship with Coursera 

Internships can be a stepping stone to a future career as a machine learning professional. Get ready for your next internship by taking a cost-effective online course through Coursera. 

Andrew Ng’s Machine Learning Specialisation offered by Stanford University and DeepLearning.AI provides a broad introduction to modern machine learning, including supervised learning, unsupervised learning, and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation.