In this article, I will take you through the complete knowledge of the interview process for a job role in Machine Learning. Here you will get all the information regarding how to apply for a job and get your interview fixed by off-campus placement drives of various companies that are going to get started very soon.
Generally, companies start with their on campus recruitment process from September, and get over with it at the end of October. Then the companies start with their off campus procedure from the end of October and which goes till mid December.
So if you are that machine learning practitioner who is not so much known college or you don’t have a degree in machine learning then you can keep reading this article.
Interview Process for Machine Learning
Now the first thing that will come into you mind is how to apply for an interview. If you are a college student and getting good companies then you may not get any difficulties in applying for a job in the machine learning domain as earlier the companies used to visit in the universities or the universities used to send the candidates to visit the company for an interview.
But now after the outbreak of COVID 19, the process has changed a bit. Now the companies are taking a virtual interview for machine learning and other technical fields over video calls and online MCQs.
The one thing to remember while giving an online exam irrespective of on-campus or off-campus, always remember never open a new tab while giving your exam if you have opened a new tab by mistake still you will be remarked as cheating, as your every activity is being noticed.
Now let’s get back to the virtual interview. The virtual interview is just like an in-person interview. The important machine learning questions that you need to prepare for your on-campus and off-campus interview process are mentioned here.
Now as I have already mentioned above the off campus interview generally starts from the end of October. So all the machine learning practitioners should start keeping an eye over online jobs websites like indeed.com, naukri.com or other websites based on your country.
Step 1: Now let’s have a look at the interview process for placement in machine learning. First, you will have an online test and a virtual interview. The online test will be based on your knowledge about the subject this is machine learning.
You should have complete knowledge of data structures and algorithms. All the machine learning algorithms and you should have an online portfolio of your projects(Github).
Step 2: After cleaning your online interview, you will be issued with a date of technical interview if you have successfully cleared the first step of your interview process for placement in machine learning. The technical interview depends on the company. Some companies prefer a virtual interview and some are still following the traditional in-person interview.
The technical interview is based on what you have written on your Resume about you. So you should write everything true about yourself. You can get all the tips about how you can prepare your machine learning resume for your interview process for placement from here.
Step 3: The next step in your interview process for placement in machine learning will be an HR Interview. This is the most important round. It is generally decided in the HR interview round that whether you will be hired or not.
In HR Interview the decision is taken on the basis of your strengths, weakness, personality and everything they will notice about you. The most important thing you need to show in this round is your communication skills, your influencing skills, and your confidence.
So these are all the necessary steps you will go across in your interview process for machine learning. Here are all the important links you need to consider:
- How To Prepare Your Data Science Resume
- Complete Knowledge of Data Structures and Algorithms
- Machine Learning projects to boost your portfolio.
I hope you liked this article on the full procedure of Interview process for the Placement in Machine Learning. Feel free to ask your valuable questions in the comments section below.