7 Powerful Steps to Land a Machine Learning Internship

Machine learning is set to grow at the rate of 36.2% CAGR by the end of 2030. An illustrious machine learning career requires you to get an early and strong start. Bagging a prestigious machine learning internship can prove to be a solid launchpad for your career to take off. Many big product companies and brilliant startups provide machine learning summer internship programs and internships from time to time.

Although, with the mammoth competition in the IT field, it has become somewhat difficult to get good machine learning internships at the beginning. So, if you’re a student or an early graduate wondering how to land a machine learning internship in India, we are here to share the best steps and advice to get you exactly that, all by yourself.

Importance of Machine Learning Internships

Before we start exploring various ways to land a machine learning internship, it’s important to understand why getting the right internship is necessary. Here are the advantages of doing an internship:

1. Practical Learning: These internship opportunities provide budding techies with an excellent chance to learn through real-life projects and hands-on learning by taking it out of a classroom. You get to understand real problems and find ways to solve them technically with real stakes.

2. Real-life experience: You get to understand the day-to-day working, the perks, and the challenges that come with the field you’re willing to pursue. It helps you grow as a professional and handle different situations and requirements better.

3. Find your interest: Machine learning is being used in most of fields today. Through an internship, you’ll get the chance to discover your preference or specialty. You can also test if you like the field or not, thus exploring your professional interests better. You’ll also get to know the kind of work environment, people, and soft skills that you need to thrive.

4. Build a Resume: Working on real projects o implement machine learning will help you gain good practical experience, thus upgrading your resume and giving an obvious edge to your candidature for your future endeavors.

5. Better connections and network: You get to meet and work with many industry professionals and experts through an internship. Leverage this opportunity to make valuable connections and contacts for life and grow your network.

All these aspects help shape your future. Hence, it’s important to find a good machine learning internship that will help you achieve all these and contribute dearly to your career trajectory.

Make sure you understand machine learning fundamentals like Python, SQL, deep learning, data cleaning, and cloud services before we explore them in the next section. You should consider joining GUVI’s Artificial Intelligence & Machine Learning Course, which covers tools like Pyspark API, Natural Language Processing, and many more and helps you get hands-on experience by building real-time projects.

Also, if you want to explore Artificial Intelligence and Machine Learning through a Self-paced course, try GUVI’s Artificial Intelligence Course.

How to Land a Machine Learning Internship in India

To land a machine learning internship in India, you must start early. Prepare an extraordinary resume to stand out. Upskill yourself with in-demand skills in machine learning. Network like crazy and do your research to target your desired internship. Prepare extremely well for your technical interviews.

The most important steps to land a machine learning internship are:

1. Research the Industry and Companies Offering Machine Learning Internships
2. Develop Relevant Skills and Machine Learning Knowledge
3. Build a strong Machine Learning Foundation
4. Craft an Impressive Resume and Cover Letter
5. Network & Connect With Industry Professionals
6. Start Applying for Machine Learning Internships Early
7. Prepare for Technical Interviews

By taking care of all the above steps, you’ll soon have an outstanding machine learning internship in no time. Sounds easy? Well, it’s easier said than done. Each of these steps needs time and learning to get them right.

Let’s discuss them in detail and make you a master of landing the perfect internship in machine learning.

1. Research the Companies Offering Machine Learning Internships

The concept of internships is relatively new in India. Fifteen years ago, there were very few companies that used to hire interns extensively in the tech field. Of course, with the changing tide of time, internship opportunities have been bustling in the IT sector.

As an intern, you’ll be usually expected to analyze the available data and use algorithms and various machine learning techniques to build prediction models accordingly. Above all, you will need to learn from your seniors and execute those learnings as per the need.

There are variations in internships as well. Common internship types include paid, unpaid, volunteering, performance-based, full-time, part-time, research, virtual, and in-office internships. Most internships last anywhere between a week to 6 months in various capacities.

Numerous product companies like Google, Microsoft, Amazon, Uber, etc. source machine learning interns directly from colleges and big premier institutions every year. Although, students have the option to find off-campus internships as well. Many potent but smaller companies put forth their opportunities through various hiring channels.

You can refer to the career page of top product companies, look for available internship opportunities and keep a tab. Popular companies for machine learning internships include Amazon, Meta, Spotify, Pinterest, Snapchat, Microsoft, Google, IBM, Intel, etc.

2. Develop Relevant Skills and Machine Learning Knowledge

Before you start seeking internships in machine learning, you need to get thorough information on all the relevant skills and knowledge that you need to put down in your resume. Research and surf through plenty of machine learning internship job descriptions online. You can also reach out to your professors, mentors, or alumni in the machine learning field to know the top skills you need to learn.

You’ll get a good idea of what the hiring managers are looking for. The key machine learning skills for an internship include knowing major machine learning tools, programming languages, frameworks and libraries, databases, strong computational and analytical skills through mathematics and statistics as well as core software engineering and data science skills. Here’s a list of various machine-learning skills that you need to learn:

1. Statistics and computational mathematics

2. Data modeling and data analytics

3. Profound knowledge of different programming languages such as Python, R, SQL, C++, JAVA, etc. to use their machine learning libraries

4. Strong foundation in data structures and algorithms (DSA), computer architecture, and other software engineering skills

5. Knowledge of machine learning algorithms, APIs, and libraries such as TensorFlow, Apache MLib, CNTK, etc.

6. Software design and architecture

7. Good understanding of basic data science, deep learning, and artificial intelligence

Apart from these technical skills, you must have various soft skills like good problem-solving, mathematical and analytical skills, time management, time management, organizational skills, attention to detail, accuracy, collaboration and communication skills, etc.

3. Build a Strong Machine Learning Foundation

You know all you need to learn. Now it’s time to build a solid base in machine learning and further build your skills from there. For starters, you need to pursue education in the tech field. If you don’t have a tech background, then you need to build your technical base from scratch.

You can take up the help of online technical certificate courses in machine learning and various disciplines included in the field. GUVI offers courses in programming languages and other topics in machine learning for beginners to help you build your knowledge from the basics.

A portfolio of competitive projects goes a long way in establishing your knowledge of core concepts in machine learning. You can build a phenomenal portfolio by participating in various machine learning competitions, events, bootcamps, developing passion projects, contributing to open source projects on Git, and becoming a part of Kaggle communities.

4. Craft an Impressive Resume and Cover Letter

Your resume acts as your introduction and first impression. Crafting an impressive resume and an effective cover letter is the key to unlocking golden career opportunities. Your resume should be simple, clear, and to the point. You can take help from various resume builders available on the internet.

Make sure to include your education qualifications, relevant skills, previous internships, LORs, projects, and certifications in the resume. If you don’t have prior experience, encash your academics, position of responsibilities, project portfolio, soft skills, achievements, and upskilling courses to create an impact.

Showcase relevant coursework during your university period. Your employer should be able to get a good idea of your technical skillset and compatibility with machine learning through your resume. Make sure to support those skills with relevant certifications or project work.

If you want to get instantly noticed, put quantified results in your resume rather than using simple power words. Your cover letter is your introduction to the employer before they get a chance to meet you. Use it to give extra insights about your soft skills and talk about your passion and love for machine learning. Don’t forget to highlight your willingness and preference to learn from that company.

Since every opportunity will be different demanding certain special skills, prerequisites, or conditions, you need to alter and furnish your resume to suit the company’s requirements. Take inspiration from the job description and include the demanded skills/specifications in your resume to make it more relevant and valuable.

5. Network & Connect with Industry Professionals

Networking is the most straightforward and effective way of getting your desired internship in record time. You can start by leveraging professional social media platforms like LinkedIn to connect with professionals, experts, mentors, and employees already working in the machine learning field. Creating a solid profile helps you track and get personalized internship listings.

Try connecting with your alumni or people you have something in common with. They might be readily available to help you understand the company’s culture, expectations, work environment, and availability of opportunities. You can grow your network of fellow machine learning professionals and relevant people and seek their help in finding a good internship at a company that you wish to work for.

Apart from social media, you can also build connections by becoming a part of ML forums, clubs, and communities. They are often rich with the latest industry information and shining internship opportunities around the corner. You also get the added benefit of classified internal information, upskilling through competitions, necessary knowledge, and tips to ace machine learning.

Various machine learning summits, webinars, boot camps, events, and meetups are other avenues to find valuable connections. You can connect with the attendees and the mentors to build contact and seek help for internships.

6. Start Applying for Machine Learning Internships Early

You must have heard ‘early bird gets the worm’. Well, it sits true for internship searches and applications. Once you get your resume ready with all the relevant information, skills, and experiences, it’s time to start applying. Identify the best internship opportunities and start applying. Keep a tab of your deadlines and subsequent emails/communication that comes your way after that.

The months from May to August are bustling with summer internship opportunities in machine learning. So, you have to ensure that your profile is ready and complete before that. To start working during a summer internship, it’s necessary for you to start applying by March-April. The screening process takes a lot of time, especially in big companies. So you want to be ready early on.

It’s a fact that large companies receive a huge volume of applications and the open positions get filled quickly enough. So, an early application makes it easier for your resume to get picked and then land an interview subsequently. Tailor the application before applying for each opportunity as per the company, job description, culture, and skills mentioned.

Big companies put out their internship hiring requirements in a more generic fashion where they match an applicant’s credentials with the available positions as they see fit. Smaller companies hire interns for specific positions as per their needs.

There are numerous other places like LinkedIn, job portals, and company websites that display internship listings. You can refer to them in detail below.

7. Prepare Well for Internships Interviews

Once your resume gets selected, you will be called for an interview. You might have to go through multiple rounds of interviews aimed at evaluating your candidature on a technical, behavioral, or cultural fit basis.

For the technical interview or test round, you should brush up your knowledge of key machine learning models and techniques along with basic knowledge of data science, deep learning, and artificial intelligence. Stay on top of software and computational skills, statistics and data analytics skills, Python, R, TensorFlow, AWS, Apache Kafka, etc.

You can practice the most asked interview questions for machine learning and prepare yourself to answer technical questions on the spot. You need to appear thorough and certain with your algorithm, mathematical data skills and top models.

You can also become a part of various coding communities that will help you keep updated with the latest machine learning developments and trends to help you sail smoothly through your interviews. You must identify your weak spots and practice eliminating them before you appear for the interview.

You must also prepare yourself to face some common behavioral and situational questions based on problem-solving skills, the ability to work on feedback and collaborative skills. Work on your communication skills consistently. During internship interviews, it’s important that you put forth your ability and willingness to learn upfront. Be confident, passionate, and earnest during the interview. Keep your responses structured and use the STAR method.

Where to Find Machine Learning Internships?

There are various places where you can find the best machine-learning internships for you. You just have to know what you’re looking for and research the legitimacy of the opportunity. Here are a few avenues where you can look for your desired internships.

1. Placement Cell and Career Counseling Centers: Make use of your college/university’s placement cells and career counseling centers. They have good opportunities from verified sources and companies, suitable for students.

2. LinkedIn companies and hiring managers often list internship openings on LinkedIn. You can create a LinkedIn profile and based on that, you’ll start receiving notifications for internships soon.

3. Internship Websites and Job Portals: Internship websites like Internshala, Letsintern, etc. have a plethora of internship postings to suit your requirements from big and small companies across India. Similarly, job posting sites such as Indeed, Glassdoor, etc. also have internship listings along with jobs. You can easily use the filters to find the perfect internships for you with so many choices.

4. Company websites: You can always check out your preferred company’s website to look for any internship opportunities available. You know they’re legit and you can directly apply for those opportunities.

Kickstart your Machine Learning journey by enrolling in GUVI’s Artificial Intelligence & Machine Learning Course where you will master technologies like matplotlib, pandas, SQL, NLP, and deep learning,  and build interesting real-life machine learning projects.

Alternatively, if you want to explore  Artificial Intelligence and Machine Learning through a Self-paced course, try GUVI’s Artificial Intelligence Course.

Conclusion

Finally, you must choose which internship serves your purpose the best way. Before applying to any internship, inspect the scope of learning a lot at that particular company. Beware of companies that seem exploitative and use students as cheap labor. Perform thorough research before applying.

Finding an internship is pretty easy if you use your resources wisely. Expand your network and knowledge. Understand the company’s requirements and tailor your resume to ensure they see you as the best fit. Keep upskilling and giving yourself the required edge with projects, experiences, training, courses, and competitions. Start early and ensure you’re well-prepared for upcoming interviews.

Just have faith in your abilities and take the first step. Rest everything will follow. If you need help upskilling and upgrading your tech career, GUVI is there to help you through your journey. Good luck!

FAQs

1. Is it hard to get a machine learning internship?

Getting a good machine learning internship isn’t easy when you’re just starting out. You need to work a lot to build a good resume and profile complete with all the relevant skills. Keep applying to more opportunities while updating and customizing your resume and cover letter to target that particular company.

2. What is the average stipend for a machine learning internship in India?

The average stipend for a machine learning internship ranges from Rs 1 LPA to Rs 10 LPA on average. However, the number is highly indicative and flexible with the size of the company, your prior internship experience, your educational institution, your area, and your course/specialization.

Large companies offer as high as 1-1.5 lakh per month for summer internships to students from premier institutions in India. While the average stipend that startups and small companies offer ranges from Rs 10,000-35,000.

3. Is an internship necessary for machine learning?

It’s technically not mandatory to do an internship in machine learning to become one. Yet, an internship is extremely helpful and usually necessary to learn the on-job skills in a real setting with actual projects and stakes. They are a huge learning opportunity for your soft and hard skills. They allow you to explore your strengths and preferences. Moreover, they also help build a stronger resume with that invaluable experience.

4. What is a good GPA for a machine learning internship?

A CGPA above 6.5-7.0 is considered good by companies for internships. Bigger companies like Apple and Microsoft need the applicant to maintain a 2.7 and 3.0 GPA respectively. Startups might not make a big deal of CGPA.

However, the role of GPA in deciding your selection declines after you’ve already done a couple of internships.
Your prior experience becomes a testament to your skills rather than your grade during an internship application. Even if you have less CGPA, you can easily win over through a good display of practical skills and knowledge during the hiring process.

5. Is it possible to get a machine learning internship without experience?

Yes, definitely. If you are passionate about machine learning and aim to learn deeply through an internship, you do not need prior internship experience for the same. Internships ideally evaluate your willingness to learn skills rather than prior experience. You can participate in various coding events, boot camps, and online developer clubs to sharpen and showcase your coding skills. You can also create a competitive side or passion project and take an online certificate course to further upskill yourself. Get LORs from professors or previous seniors to further testify for your skills in the beginning. You’ll also need to work well on your communication and collaboration skills.