Career In Artificial Intelligence: A Descriptive Guide

Ankit Sahu

2 months ago

Career In Artificial Intelligence | insideAIML
Table of Contents
  • Introduction
  • What is Artificial intelligence?
  • Career in Artificial intelligence
  • Prerequisite for Artificial intelligence
  • Machine Learning Engineer
  • Robotics Engineer
  • Data Scientist
  • AI Research Scientist
  • Jobs in Artificial intelligence
  • At The End

Introduction

          The world around us is full of tools that are now run on their own. Looking for the fastest route to the office on Google maps or saying “Hey Alexa, how to bake a cake?” or playing the playlist that Spotify has now suggested for you instead of picking your own music. 
We depend on machines and software now more than humans ever has. They’re so intelligent at what they do that you can comfortably rely on them for everyday tasks. But what makes these gadgets, software and apps so good and so intuitive? 
Well, the answer is Artificial intelligence.
And if you are someone who has an interest in subjects like Maths, statistics, computers, coding and software, then this is an industry that should definitely be on your radar. But of course, you must be saying - It’s easy to talk, but putting it into action and building a career- now that is the hard part. And you’re right. Building a career in an industry that didn’t exist ten years ago is daunting. 
That’s why we are here to make this task a little bit easier for you. In this blog, we will tell you how to build a career in Artificial Intelligence and everything you need to know about the industry. But, before we proceed into the career-building part, let’s get clarity on what artificial intelligence is. 

What is Artificial intelligence?

          Artificial intelligence (AI) is intelligence demonstrated by machines. This is not like the natural intelligence displayed by humans and animals, which involves consciousness and emotions. The objective of artificial intelligence is for machines to copy human behaviour for “problem-solving” or “learning”. All in all, machines are being enabled with AI in order to make human life easier and more efficient. And slowly but surely, multiple industries are catching on to the wonders of AI. How simply, it can do complex tasks, or how quickly it can do manual tasks that would take hours for humans to do. 
As more industries adopt AI, the career prospects are just ripening and exploding as the year's pass. So here are some things you need to know and do if you want to start a career in AI. 

Career in Artificial intelligence

          AI has been a good career choice for a while now, and as the adoption of Artificial Intelligence in various fields continues to grow, the demand for trained professionals/experts to do these jobs created by this growth is also skyrocketing. AI is soaking up not just industries like computers and IT- but also various other industries like hospitality, education, finance, and engineering. 
An important step is to hold a Bachelor’s degree in mathematics and computer science. If you have an existing career in these fields, then that is a good starting point too. Being in the right field is imperative as AI is an industry where one needs skilled expertise.
If you’re already a software engineer or a developer, it becomes a bit easy for you to enter the AI industry as compared to those who are just getting started. 
It’s true that most of the time, a Bachelor’s degree only lands you an entry-level position or an internship, but it will at least get you started. Once you get into the AI industry and understand how things work, you can switch to another company and get a good hike. If you want higher positions that entail supervision, leadership or administration, you need to have a master’s degree, a Doctoral degree or five or more years of experience. 

Prerequisite for Artificial intelligence

Prerequisite for Artificial intelligence | InsideAIML
        As they say, without a strong foundation, you cannot create anything of value. AI is an advanced science and has certain prerequisite subjects that one needs to be aware of. So it is important to have information and knowledge about certain subjects such as these shown on the screen before you dive headfirst into AI.
To elaborate more clearly, understanding the logic of a problem and then solving it lies at the heart of AI. To do this, solve logical reasoning problems and play mobile and computer games like chess and sudoku, which involves trivia and puzzles. 
Then moving to algorithms, which are also the brain of an AI system, involves many complex structures. So to get a hands-on these, try writing pseudo-codes. There are plenty of free websites like Pythondone and Programs available to test your homegrown skills. 
Lastly, data acts as the blood in the AI system and this data is efficiently carried by Python, so learning Python codes is more of a necessity than a luxury here. Start to write simple Python programs and try to understand how to collect the data and process it with the help of Python libraries like NumPy and Pandas. Though this is enough, getting the know-how of small POCs like the Titanic data set can keep you ahead of the competition. 
Okay, so now that you know what fields to study in and get a hold of so…What specific jobs await you in AI? Let’s take a look at some popular ones. 

Machine Learning Engineer

Machine Learning Engineer | InsideAIML
          Machine Learning engineer is considered to be one of the most sought-after careers jobs in the AI space. To be a machine learning engineer, one must have a strong hand in IT skills, have the knowledge of applying predictive models and utilising natural language processing while working with huge datasets.

Robotics Engineer

Robotics Engineer | InsideAIML
          A robotics engineer or scientist builds mechanical devices to perform various tasks using AI, such as robots from Boston Dynamics — whether it is about machines to go where humans can’t reach or robotic hands for microscopic tasks such as operation theatres. A robot might automate jobs, but the industry requires robotic engineers who can create robots. 

Data Scientist

Data Scientist | InsideAIML
          A data scientist collects, analyses and interprets data from various sources by using data science tools, machine learning and predictive analytics to understand better how the business performs and builds AI tools. To be a data scientist, you should have expertise in using Big Data platforms and tools and should have a strong hand in programming languages such as Python. 

AI Research Scientist

AI Research Scientist | insideAIML
          A research scientist mostly is responsible for designing, undertaking and analysing data from controlled laboratory-based investigations, experiments and trials. To be a research scientist, you should have a strong knowledge of different AI disciplines.

          The final step to building a career in AI is finding a job in AI. And how can you do that? So, let’s walk you through it. 
There are various job hunting portals/platforms that would help you land your next job in the field of AI. The top 3 are Indeed, LinkedIn, and plain and simple Googling.
If you have a strong CV, have updated your resumes online with relevant information, and have followed basic hygiene when building these resumes, then applying for jobs online is as easy as it can get.
The reason applying online is so easy is because the AI industry is tech-forward. So no reputed company will be inactive online. You will find all you need to know through the company’s website, Facebook, Twitter or LinkedIn. Additionally, Most companies across the world list their jobs online. When was the last time you found a job offline?
Also, you get the direct contact information of the people you want to work with through most websites. They are just an email or message away! The only hard part about applying online is just gathering the courage and putting yourself out there- making that CV, shooting that email, calling that number. 
Once you have done that, it just becomes easier. You get to understand what hiring managers are looking for, what openings are present in the market, and what locations have the jobs. All this information helps you network better in order to get a job. But if you are in the thinking phase and needs some assistance in transitioning your career to AI. Have a word with us. Just leave your contact details in the comment section below or reach out to us on this number. 

At The End...

          So that is it. These are some of the preliminary steps you need to follow in order to build a flourishing career in AI. The basics are pretty simple- build a knowledge base and then network online within the industry. Once you follow this simple process, a career will most definitely fall in place. 
We hope this blog was helpful. Do let us know if you have any questions or doubts in the comments below, and we’ll do our best to answer them. For more such blogs on AI, ML and more, keep following our blogs.
   
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