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How to build a strong AI Resume: A complete guide

In today’s competitive world, when the companies are pressing hard to find talented people, it has become very important to stand out in the crowd to show what qualities you possess. One way to do this is through a resume. As it is the first thing through which a hiring manager will search for talent. We all are aware of stringent rules of eliminating candidates by just looking at resumes. So, it is very important to design your resume in the simplest yet the most articulate manner. It must contain all the details in accordance with the job profile you are applying for. For a machine learning job profile, most companies look for a candidate with diverse talent starting from basics to high-level coding ability and machine learning skills. So that a candidate can work on varied projects.

A complete guide to build AI resume
Source – Google

This article will focus on various topics that focus on how to build a strong machine learning resume. Following is the list of sub-topics which will help you build an impressive machine learning resume,

1. General Tips

2. Must have skills for an AI resume

3. Non-Tech skills for AI resume

4. Employers point of view

5. Machine learning resume

6. Resume samples

So, let us explore each of the sub-topics in detail to build a skill-oriented and impressive machine learning resume.

Resume tips
Source – Unsplash

1. General Tips:

The formatting of the resume plays an important role. Specifically, when you can’t experiment much with the format. And want to keep it simple but also want to make it stand out. In such a case, the following tips will be useful-

a. Keep it simple

We all get creative while trying to make our resume eye-catching. But the core ideal of resume building is to keep it as simple as possible by using basic fonts that are pleasing to eyes with font size around 10-12. You can play with different fonts and text sizes for differentiating. Do not fill every part of your resume as it may look too clumsy and try to use simple vocabulary with short sentences. Try to confine your resume in one or two pages but with relevant information.

b. Stand out carefully

One should have two resume formats ready all the time. Because, when you apply through ATS, you have to keep the format standard so that the computer can read it properly. And if you are applying through any other means, you are free to add some design elements, bullets, or color your text to make it pop.

c. Include Your contact info

Make sure you have added a phone number and your email address. Also, you can add your LinkedIn profile provided you have maintained it suitably for employers. Adding your address is not required anymore.

Pro tip: Browse through AI job opportunities. Read the job description. Especially, read the requirements to get an idea about the specific qualifications that you need for the job.

artificial intelligence
Source – Unsplash

2. Must have skills for an AI resume:

Artificial intelligence is considered highly scientific as the task is to mimic the human brain by using machines. To pursue a career in artificial intelligence, the skillset that you need is varied. As career types available in AI vary from algorithm developers to hardware technicians. So it becomes very important to personalize your resume according to the career you are looking for. We have categorized the different skills requires in the AI resume into two main categories.

 Must have skills for an AI resume
Source – Unsplash

A) Mathematics

An AI engineer should have good skills in math. The subtopics include statistics, probability, calculus, linear algebra, Bayesian algorithm, and logic. So, let us, deep-dive, more into each topic

a. Probability and Statistics

Statistics is the field that handles the collection, analysis, presentation of the data in a suitable form. Data plays a very big role in AI. Most of the AI works for circles around collecting the relevant data, cleaning it, and putting it into various algorithms.

In statistics, knowledge of probability distributions, statistical significance, hypothesis testing, regression, Bayesian thinking, conditional probability, priors and posteriors, and maximum likelihood are important. It is not necessary to learn of all the above-mentioned topics all at once. But try to get a thorough understanding of most. Mentioning some of the above topics gives the impression that you have a strong base to work on AI.

b. Linear Algebra and Calculus

Linear Algebra is the key foundation in the field of machine learning/AI. It is the sub-field of mathematics that deals with matrices, vectors and transforms. The extent to which you should learn linear algebra depends on your focused work. If you are going to apply for machine learning algorithms directly, then basic knowledge will be sufficient. But if you are planning to create something new from scratch and want to focus on R&D then deep knowledge of Linear Algebra is vital. To improve your functionality in AI, a few linear algebra topics such as Notation, Operations, and matrix factorization are important.

Calculus plays a major role in many of the machine learning algorithms. As a data scientist, one always gets curious about how a particular algorithm works. Calculus will help you understand machine learning algorithms such as gradient descent, backpropagation, etc. You must include the above-mentioned topics to show your grasp on the basics which will highlight your profile.

Mathematics section in AI resume
Source – Unsplash

B) Computer Science

To work on any AI model, fundamental knowledge of computer science is important. The subtopics include data structures, programming languages, programming skills, machine learning, etc. Let us discuss thoroughly each subtopic to know the scope and impact on your resume.

a. Data Structures

Data is an essential part of machine learning. As most of the machine learning work circles around collecting, arranging, and cleaning of the data. So, one should have strong knowledge in working with complex data structures like trees and graphs, big data analytics, and complex computation. Thus, you should mention the above skills in the resume in the form of working experience or projects you have done while learning. Also, it will add more benefits if you have any course certificate or diploma that can be added to the resume.

b. Programming languages

Learning programming language to apply for a job in machine learning is very important. There are many languages available. But you must learn a language that has essential features and libraries to work on the machine learning model. Some programming languages available are centric towards machine learning. By learning those languages you can have an upper hand on AI. Languages like R, Python, are considered most suited for developing any machine learning model. As most of the libraries have been developed which support these languages. With time, ML libraries have also been developed in C/C++ as sometimes speed and memory are critical. For the data science field in machine learning, R is the best-suited language.

Python is one of the best-suited languages for machine learning. The functionality Python has shown in machine learning is tremendous. Also, the easy syntax makes it easy for any programmer to learn and excel in Python. Libraries that Python provides are very useful for machine learning purposes. Libraries such as Scikit-learn, TensorFlow, Keras, etc. are dedicated to machine learning. Here are some more reasons why python?

So, learn at least two programming languages and mention those programming languages in resume along with various libraries that you think are important for the job you are applying for.

c. Machine Learning

After learning programming languages from various online and offline sources, it is time to concentrate on machine learning. Machine learning is the base of whatever career you choose in AI. So, it becomes very important to master machine learning models, types, algorithms, and supporting libraries. There are three types of machine learning based on how a machine learns: Supervised Learning, Unsupervised Learning, and Reinforcement Learning.

If you are experienced in the field of machine learning, you can mention the models on which you have worked and try to cover all the three types. If you are fresher and don’t have any experience, you have to practice different machine learning models which you can do on various examples available on Kaggle and Dataquest. You should practice all the algorithms so that you can mention it in your resume and also practice it on various data sets available on the free source which will help you build confidence. At least one example from each machine learning type should be mentioned in the resume.

machine learning
Source – Unsplash

3. Non- Tech skills for AI resume:

There are varied types of careers in the AI industry so there are certain skills required apart from technical skills. By mentioning such type of non-tech skills, you can further embellish your profile. Most AI professionals are:

  • Critical thinker – Machine learning focuses more on data and sometimes fitting the model can be a very tedious task and requires trial and modify method. In such cases, critical thinking is a quality that every employer looks for as this quality helps to take some concrete decisions.
  • Curious, Problem solver and innovator – As we all know that AI is an emerging field and now and then improvements are happening around the world. To work in this field, one has to be very curious about learning new developments and try it on their own to know how things work and how work can be automated.

Pro Tip: Do not hesitate from giving all possible details about your work experience and achievements. Flaunt what you have achieved.

Non- Tech skills for AI resume
Source – Unsplash

4. Employers point of view:

Apart from above all technical and non-technical skills, there are basic particulars that can enhance your resume and will provide more information about you to the employer.

  • A bachelor’s degree in either computer science or diploma in a related field or any field with a note explaining what has driven you towards artificial intelligence.
  • A section dedicated to achievements and developments you were involved in (it’s okay to brag a little about your achievements*)
  • Relevant tools and software like Anaconda (Jupyter, Spider, R-studio), PyCharm, Eclipse functioning.
  • General background knowledge of neural networks, NLU, NLP, chatbot, deep learning, video analytics, etc. according to the job you are applying for.
Employers point of view
Source – Unsplash

5. Machine Learning Resume:

After finishing all the prerequisites required for AL resume, it’s time to set an editable format for your resume with all the skills and achievements together in a well-planned format by taking note of the tips that are mentioned in the first section of this article.

There is a pattern in the resume that most people follow. You can interchange the middle order but it should always start with the header, personal summary, and ends with skills and references. Al resume should include-

1. Header

The header should contain your name, address and contact information(Phone number, Email, LinkedIn*)

2. Personal summary

This is an opportunity to impress the hiring manager within 3-5 lines where you have to describe who you are and what you have achieved. Here you have to express yourself and flaunt a little about why the job perfect for you by quoting your achievements.

3. Experience

This section is very important and probably any employer will look at this section first before any other section. You have to mention all experience relevant to the job you are applying for and also do mention the period for which you were employed. If you do not have enough experience, you can still mention the internships related to the job you are applying for.

4. Projects

This is a very important section for freshers. As you won’t be able to populate the experience section, this section will balance the resume. As mentioned in the above prerequisite, you should add projects you have done online or on platforms like Kaggle and also explain your contribution in terms of efficiency or performance.

5. Education/Certificates

In this section, you have to mention your degree and all the professional learning certificates. Experienced people are not supposed to mention grades but as a fresher, you must mention your grades if it is more than average.

6. Skills

All the skills you were not able to showcase in the experience and project, you should incorporate it here. Skills mentioned in section two and three should be mention in this section.

7. Reference

This is an optional section. Here you have to add the contact information of two to three people with their permission who can speak on your behalf on your work ethics.

AI resume
Source – Pyiterator

Well if you loved it, Don’t forget to CLAP !

If you want couple of resume examples to get your creativity flowing, Please Do comment below.

Thank you Aliens !

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