How to Land a Machine Learning Internship
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One of the best ways to get a foothold in any industry is by doing an internship. This is especially true in the fast-moving tech space. A machine learning internship will give you the chance to learn directly from machine learning engineers, which gives you valuable practical experience and also helps establish a strong professional network.
If you want to be a machine learning intern, you need to be prepared to put in the time and effort to find a suitable position. These roles don’t come easy, and most companies only hire the very best candidates.
For current students and recent graduates, the road ahead isn’t always straightforward. In this post, we’ll clear up the confusion and explain everything you need to do to land the machine learning internship you’ve been dreaming about.
5 Essential Hard Skills for a Machine Learning Internship
The current demand for people with skills in AI and machine learning greatly exceeds the supply. Despite the great benefits and top-level pay packaged, a tech talent shortage has left many roles unfilled.
However, while the talent pool may be limited now, things are set to change. We are already seeing more innovative talent development initiatives from major tech giants, such as the deep learning course offered by Google. These are designed to encourage more people to enter tech roles, and so, the competition will grow.
Which makes this the ideal time to go after a machine learning internship. While an internship is an opportunity for you to pick up new skills, there is a certain level of technical expertise you’ll need to possess even at this level. Here are five core skills that companies will want their new machine learning intern to possess.
Python is the go-to programming language when you get started in machine learning, so you must be adept at that at the very least. To really boost your chances, you should develop high-level abilities in other common languages, especially C++ and Java.
Probability and Statistics
Probability and statistics are an integral part of machine learning jobs. If the idea of reading theories like the Gaussian Mixture Models doesn’t excite you, then this may not be the job for you. Get acquainted with theories like these to truly solidify your knowledge.
Applied Math and Algorithms
Machine learning is all about algorithms. You must understand how each algorithm works. Aspects like convex optimization, gradient descent, and partial differential equations should be easy for you.
Machine learning engineers will create systems that are easy to integrate with existing ecosystems and components. When companies look for a new machine learning intern, they’ll want to find somebody with a strong background in APIs.
Advanced Signal Processing Techniques
A crucial element of machine learning is feature extraction. Not every problem has the same solution, and so we can experiment with a diverse range of signal process algorithms like bandlets, curvelets or wavelets. The more you know about these advanced techniques, the stronger your application will be in the eyes of employers.
3 Personal Qualities of a Machine Learning Intern
Aside from the technical nous, there are some other key areas (soft skills) to develop before you can secure a machine learning internship.
Tech is advanced rapidly, with artificial intelligence, augmented reality, and machine learning-based software in just about every industry on the planet. It’s important that you keep up-to-date with industry news and major changes.
You should be active in online communities, partaking in discussions, and following major influencers, blogs, and tech news sites. There is also a treasure trove of excellent free resources online to improve your machine learning knowledge, so you can continue your education by reading papers like Google Bigtable and The Unreasonable Effectiveness of Data.
Critical and Creative Thinking
Having an analytical mind is vital, as you will be dealing with reams of information that requires you to think logically and apply set standards in order to discern patterns or results.
Further to that, you must also be able to develop innovative new methods and approaches to formulating problems and solutions.
A Can-Do Attitude
If you’re going to be a part of the machine learning industry, you need to have a positive attitude that embraces complex challenges. Remember that internships are a company’s way of testing out people for a full-time role.
Employers that offer a machine learning internship want to find people who can grow with their company. You should keep that in mind when you start an internship, understanding that you need to go above and beyond to prove yourself worthy of keeping.
Where to Look for a Machine Learning Internship
So, you’ve got the chops. Now, you need to know where to look for that coveted machine learning intern role.
The best method is to make an extensive list of all the companies you will target. Explore each company’s website, learn about their brand, their culture, and their mission. Is this something you truly want to be part of?
Aim to compile a list of around 30-40 companies, then delve into what they need. How will you add value to their machine learning department?
Here are a few places worth checking out to build up your shortlist.
- Meetups: If you’re still in school, look at associations at your university that organize professional networking events. You can also find events in your city on sites such as Eventbrite and Meetup. Look for machine learning events, especially if you’re in a major metropolitan area. Events taking place outside your university will have a mixed crowd where students, young professionals, and managers will be in attendance.
- LinkedIn: It’s imperative that you develop your online professional network. You should be doing this from your time in school, connecting with like-minded individuals on the same career path, including students, tutors, and industry veterans whenever the chance arises. A strong network will guide your efforts and may serve up some excellent referrals when you need them most.
- Google Search: There are a lot of great blogs and online communities for budding machine learning engineers to learn from. For example, Kaggle is the perfect training ground to cut your teeth in machine learning. By contributing to the community and developing your own side projects, you can build up your skills and learn about new opportunities from other members.
Study the machine learning job descriptions for each company on your shortlist. Highlight the keywords in each description, and make a list of terms that are shared across multiple jobs and companies. Consider the qualifications and desirable skills that companies look for.
How do you stack up? If you are lacking in basic requirements, you may need to develop your skill set through a volunteer role or an online course before you can apply for an intern position.
How to Interview for a Machine Learning Internship
Interviews can be nervy affairs. We understand it’s a big deal to meet the gatekeepers to major tech companies with the hope that you’ll be welcomed into the fold at the end of a short meeting.
Chances are they will meet a lot of people hoping to become their next machine learning intern. By knowing what to expect ahead of time, you can put your best foot forward.
Display Logical Thinking
Quite often, your portfolio can demonstrate technical proficiency, but it doesn’t always let people know how you think. When the interview questions turn technical, take the chance to show your logical approach to tasks. Highlight a previous example from a past project, explaining it in the following structure:
- 1-2 previous methods
- Your approach
- End result
Understand the Need for an Intern
You should know why the company is hiring an intern. Go through the entire job ad with a fine-tooth comb, then explore the company’s website, social channels, and LinkedIn page. Look for recent news on developments within the company, such as a change in hierarchy or the launch of new marketing campaigns, products, or initiatives.
This research can help you understand the motivations for a company wanting to hire an intern. By going into an interview with some context and understanding of your potential value, you have a better chance of selling yourself as the solution they need.
Identify a Core Problem
Ideally, you shouldn’t apply to any company without doing sufficient research on them. If a company asks you to interview, it’s vital that you dig deep to discover as much about them as possible. This boils down to the following question:
What is a specific core problem you can solve for this company?
This question should drive your research, and help you prepare the challenges you may face in this role. Moreover, it can be the defining aspect of your interview that sets you apart from other candidates.
Get Familiar With How They Operate
Many companies will have a blog or an active social media platform where they discuss company news, including major challenges, successes, failures, and innovative new ideas. This is a goldmine for your research, and it will also give you insight into how they operate. Be prepared to discuss their approaches, tools, and data sources in the interview.
Be Ready to Brainstorm Machine Learning Solutions
Nobody expects a prospective new intern to strut into an interview and rhyme off a detailed solution to something the company has struggled with for years. However, when you have done your research, you will know a few things about the company:
- Why they need an intern
- A core problem they have
- Their current operations
With all that in mind, you must think about how machine learning can fit in. Interviewers will take note of people who display a genuine curiosity about the problems they face, and will be impressed by those who show motivation to find a solution.
What Comes After the Internship
A machine learning internship is a big step toward a career in one of the most innovative industries in the digital age. If you impress your employer, they may hire you for a full-time role, or at the very least, give you a great referral so you can secure a position elsewhere.
If neither happens, don’t wait around for a job to fall in your lap. Here are a few ways to use your internship as a springboard to greater things.
If you don’t already have a website that hosts your machine learning resume and showcases your skills, then you definitely should create one after your internship. This gives you a live platform to discuss your experience and highlight your technical abilities in the field.
Whether it’s on your portfolio site or a separate entity, a blog is a huge asset in creating your own brand. Here, you can discuss the responsibilities you have been given during your internship, detail the machine learning projects you completed, and explore how your work delivered real value for the company.
After your internship, you should build upon the experience with more courses and self-directed study, for example:
- Free courses like the Introduction to Deep Learning course from MIT.
- Offline classes, if you live near a major metropolitan area.
- Online courses, like Springboard’s Machine Learning Engineering Career Track, which comes with a job guarantee.
Once you have the grounding of an internship, your online freelance profiles will carry more weight. Platforms like Upwork may be competitive, but you can find great opportunities for long-term work and well-paid side projects that enable your portfolio to grow.
A Machine Learning Internship Gives You an Edge
The process of landing a machine learning intern role is a time-consuming endeavor. It may take many rejections before you receive a positive response. However, don’t let that deter you—eventually, you will land some interviews. After that, it’s all about proving your worth, from the interview to the internship itself.
With a positive attitude and creative mind, you can build a solid portfolio of work and develop your personal brand in a way that will make you a standout choice for many companies who want a machine learning intern. You don’t need to wait until after your internship to take these steps—a proactive approach will get you where you want to be faster.
AI will continue to transform our world for many years to come. Therefore, machine learning graduates who bolster their portfolio with an internship will be in high demand. Ultimately, they will have a clear edge going forward in their careers.
If you want additional career-focused training, check out Springboard’s Machine Learning Engineering Career Track, the first of its kind to come with a job guarantee.