- Tips to make machine learning resume
- What are the must-have skills for an AI resume
- How to master programming languages
- What employers look for on an ML Resume
- Creating your Machine Learning Resume
- Machine Learning Fresher Resume
- Machine Learning Engineer Resume
- Machine Learning Resume Sample
Tips to Make Machine Learning Resume
Companies today, are hard-pressed to find good machine learning talent. Any specific skill requisites, of course, depend on the machine learning roles and profiles, but some skills that must be present on your machine learning resume are consistent across profiles. Mostly, companies want candidates who already come with a large pool of diverse machine learning skills, theories and coding ability so that they can cross function on ML projects if need be.
Experts of this domain not only need to have a sound knowledge of Machine Learning algorithms and when to apply what, but also how to integrate and interface. The core skills required are technical, with a good understanding of mathematics, analytical thinking and problem-solving. While the specific skill requirements for each profile differ, there are core ML skills that are constant for all roles.
That being said, there’s nothing like a certificate when it comes to buffing up your ML resume. This will also improve your chances of getting hired. Check out Great Learning’s PG program in Artificial Intelligence and Machine Learning to upskill in the domain. This course will help you learn from a top-ranking global school to build job-ready AIML skills. This 12-month program offers a hands-on learning experience with top faculty and mentors. On completion, you will receive a Certificate from The University of Texas at Austin, and Great Lakes Executive Learning.
I will open this article with some quick tips, and then we will discuss how to create an impressive machine learning resume in detail. So, here are some of the tips:
- Use clutter-free design and do not fill every part of your resume with text
- Using bullet points wherever possible is a better practice as compared to paragraphs
- Always use active voice
- Use simple vocabulary and shorter sentences
- Do not try to fit in everything on one page. Use more pages if you feel the need for it but keep the number of pages as limited as possible.
- Edit until you get a draft which is concise, clear in understanding, looks good visually, and includes all that you want to tell the recruiter about you
- Use online tools such as Grammarly to self-check your draft
- Have it proof-read by a third party, preferably a friend or a daily member who would give you genuine advice
Click below to download your machine learning resume template
What are the Must-Have Skills for an AI Resume
Probability and Statistics
The theories of probability are the mainstays of the most machine learning algorithm. Being familiar with probability enables you to deal with the uncertainty of data. Getting a grasp of the probability theories like Python, Gaussian Mixture Models, and Hidden Markov Models; is a must if you want to be considered for a machine learning job that centers around model building and evaluation.
Closely linked to probability is statistics. It provides the measures, distribution and analysis methods required for building and validating models. It also provides the tools and techniques for the creation of models and hypothesis testing.
Together, they make the framework of the ML model building. This is the first thing to consider when building your machine learning resume.
Computer Science and Data Structures
Machine learning works with huge data sets, so fundamental knowledge of computer science and the underlying architecture is compulsory. Expertise in working with big data analytics, and complex data structures, are a must. Thus, a degree or a formal course in these domains is required for a machine learning career. Your resume must display your skills at working with parallel/distributed architecture, data structure like trees and graphs, and complex computations. These are required to apply or implement, at the time of programming. Additional certifications for practising problems and coding will hone your ability with big data and distributed computing. Experience in computer science applications will go a long way in securing you a job in this field.
Programming Languages – R, Python, Java
To apply for a job in Machine learning, you are required to learn some of the commonly used programming languages. It implements any language with the essential components and features, even though it is largely bound by concept and theory. Some programming languages are considered especially suited to complex machine learning projects. So, working knowledge of these programming languages adds value to your machine learning resume.
Using C/C++ when memory and speed are critical, helps to speed up the code. Many ML libraries are also developed in C/C++ as they are suited for embedded systems. Java, R & Python work very well with statistics. Python has several machine learning-specific libraries that make use of efficient processing, despite being a general programming language. Knowledge of Python helps train algorithms in various computing architecture. R is an easy-to-learn statistical platform, it’s use in ML and data mining tasks is increasing.
How to Master Programming Languages?
A degree, certificate or online diploma in these languages, ensure a good resume. As an engineer or student of science, you may already be skilled in C++, Java, and Python. You can also learn these languages online in your spare time, and practice on projects for special mentions on your CV. Programming languages like Python and R make it easy to work with data and models. Therefore, it is reasonable to expect a data scientist or machine learning engineer to attain a high level of programming proficiency and understand the basics of system design.
Read Also: 100 Most Common Machine Learning Interview Questions
- Machine Learning Algorithms: Applying machine learning libraries and algorithms is part of any ML job. If you have mastered the languages, then you will be able to implement the inbuilt libraries created by other developers for open use. For instance, TensorFlow, CNTK or Apache Spark’s MLib, are good places to work upon. You can also begin with practising programming algorithms on Kaggle. You can mention this in your ML resume as well.
- Software Engineering and Design: Software Engineering and System Design, are typical requirements for an ML job. A good system design works seamlessly, allowing your algorithms to scale up with increasing data. Software engineering practices are a necessary skill on your resume. As an ML engineer, you create algorithms and software components that interface well with APIs. So technical expertise in software designing is a must while applying for a machine learning job.
What employers look for on an ML Resume
Apart from the must-have particulars, here is a basic checklist that can enhance your resume.
- A Bachelor’s degree in either computer science or in a related field.
- A good amount of prior experience with GPU computing and data mining.
- A general background in NLP and deep learning, along with their corresponding tools and techniques.
- Basic experience with agile software development practices.
And finally, some character traits that are looked out for also include:
- Analytical and critical thinkers
- Data-driven performers
- Clear communicators to translate and understand complex information
- Problem solvers and innovators
Creating your Machine Learning Resume
Now that you have an idea about the required skills and prerequisites for a career in Machine Learning, the next step is to put it all together into a well-planned resume. It is important to keep some general tips in mind, including:
- There is no need to downplay your achievements and success. If there’s a place to boldly talk about your accomplishments, it’s on your resume.
- There is no need to fill every inch of your resume with text. White spaces provide a cleaner look to the document, making it much easier for the reader to comprehend. A good idea will be to adapt existing templates online, that equate well to your preferences.
- Ensure that the writing is concise and to the point; eliminate any extra verbiage, unless necessary.
- Do not confine your resume to a single page, there is no one-page mandate. As long as there exists relevant experience, the extra room is justified.
- Have it proofread, either online (on tools like Grammarly) or by a family member. This is useful to spot unseen errors and provide an outside perspective.
Important information that your Machine Learning Resume should include are
- Personal Summary
Machine Learning Fresher Resume
When it comes to freshers, of course, they have no experience to showcase. Here, you focus more on your projects, certifications, internships, technical skillset, and soft skills.
The important skills to showcase on a resume are:
- Programming skills
- Data modelling and evaluation
- Machine Learning algorithms and libraries that you have worked with
The soft skills are the ones that make you an ideal employee and help the company function better. You can mention select accomplishments that showcase these skills, such as:
- A time you were a valued team member
- A time where you lead a team
- The specific problem you identified and solved
- When you followed directions
- A scenario where you stepped up beyond your responsibility
Explicitly explain the following points in your resume:
- Machine Learning Projects with objective, approach and results.
- Knowledge of any programming language
- Proven expertise in solving logical problems using data
- Training or internship in data analytics or data mining
- Highlight if you know Python or R
Your resume should be structured like this:
- Resume heading
- Personal and contact details
- Career objective
- Technical Skills and Soft Skills
Creating a Machine Learning Engineer Resume
While creating a resume to apply for the role of machine learning engineer, keep these things in mind:
- Read the job description thoroughly and edit your resume to make it relevant to that particular job opening
- Mention all the skills that you have learnt and would be useful for you to pursue the role
- If you think there are some skills or small certifications that you do not have, acquire them and then add it to your resume
- Highlight your previous designations and work experience
- Clearly mention how will that experience help you perform well at the job
- Mention rewards and appreciations received in your previous roles
- Add successful projects in your achievements section
- Do not forget to highlight soft skills
- Provide a glimpse of professional training attended or given if any
Machine Learning Resume Sample
An application for machine learning job role requires careful planning and consideration. Machine learning is all about algorithms, which in turn stems from a good knowledge of big data analytics and requisite programming languages. Sound engineering or technical background is a must. By including these skills in your machine learning resume, you are increasing your chances of being selected. So, are you all set for a career in machine learning?
You can also upskill with Great Learning’s PGP Artificial Intelligence and Machine Learning Course. The course offers mentorship from industry leaders, and you will also have the opportunity to work on real-time industry relevant projects.
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