Machine Learning is an application of artificial intelligence that creates systems with the ability to robotically learn and improve from experience, without being programmed for each individual experience. A Machine Learning Engineer enables this automation through computer programs, which use data to undertake a specific task in business or research. How to become a Machine Learning Engineer, though? Why is it important?

For almost a decade now, we have been talking about Artificial Intelligence and Machine Learning changing the course of conducting business. Today, it has become a reality and the future is promising and encouraging. There are several wonderful courses being offered to help job seekers address the basic question of how to become a Machine Learning Engineer. 

Unlike the traditional way of doing business – with a specific focus on cost and statistics, today, the world of business, be it a large organization, or a start-up – make use of Machine Learning, Artificial Intelligence, and Data Science. These buzzwords play a key role in business decision making. The demand for Machine Learning jobs and jobs in related fields have increased manifold, and the Machine Learning future is bright. This is paid testimony, from the below-mentioned graph, released by Monster.com. 

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How to Become a Machine Learning Engineer?

In order to become a Machine Learning engineer, you must know how to create, read, and edit computer code. Being familiar with languages like Python is a must. You must complete relevant Machine Learning courses and go through online Data Exploration courses. Earning a relevant degree, or certification is a bonus and should help you land a job as a Machine Learning engineer. Let’s dig into what a Machine Learning engineer does. The main purpose solved by a Machine Learning Engineer is to create a solution to solve business problems. For scalability and optimization, Machine Learning Engineers optimize their solution based on various data and inputs. 

They run marketing campaigns, improve product services, and conduct customer satisfaction activities to increase customer involvement, and generate revenues. All this is done, while contributing to the fields of Artificial Intelligence and Machine Learning, through their research and implementations. 

Prerequisites to Become an ML Engineer

The world is unquestionable, altering in rapid and melodramatic ways, and the need for Machine Learning engineers is increasing day by day. If you dream to become a Machine Learning Engineer, the fundamentals of programming and algorithms are something that you cannot miss out on. 

Sorting, searching, optimization, memory, cache, deadlocks, and bandwidth are concepts that you may need to master to excel in your Machine Learning profession. The Machine Learning Future is bright, and it is essential that you know all the aspects of the job, and the skills required for the same. 

How to become a Machine Learning engineer? We have got you covered. Here are the skills, and the mindset required to be a Machine Learning engineer. 

  • Mathematical Skills

Mathematical play an important role in understanding the working of Machine Learning, and the use of different algorithms for business problems. 

Three of the most important concepts you need to understand are – 

Probability – Bayes Theorem, Probability Distribution, Sampling, Hypothesis Testing.

Linear Algebra – Matrices (To Perform Simple Operations) & Vectors (To Analyse Customer Behaviour)

Calculus – Differential Calculus and Integral Calculus. These helps in determining the probability of events.

  •  Develop Good Programming Skills

Knowledge of R, Python, Java, C, C++, and other languages is essential. Python & R are the best languages for coding a Machine Learning algorithm. Python is Object-Oriented and R is a Functional-Oriented language.

  • Data Engineering Skills

These skills help you process and analyze data. A Machine Learning engineer needs to work on the available data set and create patterns that will be useful for the business in question. Knowing integral aspects of data modeling and evaluation will certainly help a Machine Learning Engineer in evaluating various models.

It is also recommended to have been familiar with libraries like Tensorflow, PyTorch, Scikit-learn, and Jupyter. For a Machine Learning professional, it is a bonus to know about basic algorithms, memory management, and the linking process.  

Tensorflow – An open-source, free software library used for differentiable programming, and data flow, across a wide range of tasks. It is used for Machine Learning applications, like neural networks.

PyTorch – An open-source Machine Learning library that is based on the Torch library. It is used in several applications, like natural language processing, and computer vision.

Jupyter – It is a project that helps support execution environments, in several programming languages.

With this outline of Machine Learning skills, the question of how to become a Machine Learning Engineer must seem a little less tricky. To know about the type of interview questions, you may need to answer, visit this blog – 41 Essential Machine Learning Interview Questions

 Now, that we have an understanding of how to become a machine learning engineer. Here are some bonus points on various machine learning jobs and opportunities that the industry has to offer.

Machine Learning Job Opportunities

The Machine Learning engineering job graph is increasing at an exponential rate, well above Big Data and Cloud Computing opportunities. Machine Learning jobs are increasing day by day and Machine Learning engineers are financially well off. Organizations are interested in investing in people who are skilled in the art of Machine Learning, and the Machine Learning future is bright indeed – The industry is booming and blooming.

Day-to-day innovations are highly dependent on Machine Learning. Internet giants like Google, Facebook are embedded around Machine learning and its applications. The scope is tremendous and advancements in Machine Learning will make a big difference in every field. You can bag a job as a –

  1. Machine Learning Engineer
  2. Computational Linguist, 
  3. Data Scientist 
  4. Designer in Human-Centred Machine Learning
  5. NLP Scientist
  6. Business Intelligence Developer

There are several other amazing job opportunities in subsets of Machine Learning and its applications. 

According to a report by Indeed, one of the world’s leading job opportunity websites, Machine Learning jobs are the most in-demand jobs in 2019, as they offer great salaries, enormous growth potential, and varied applications. In fact, the Machine Learning field boasts of a gross increase in salary of 344%, since 2018! Quite impressive!

Machine Learning Future: Bright and Encouraging 

The best part of taking a career in Machine Learning is that the applicability of the job seems to have a huge scope, as the technology gets more advanced, and we better understand how to use the data we generate. Fields like education, healthcare, IT, and manufacturing, among others, are going to be further disrupted with the applicability of Machine Learning. In the future, there is going to be no field left, to which Machine Learning doesn’t apply. 

 To sum it up, the best have characteristics, to be a successful machine learning engineer are mentioned below. You must build these characteristics, and the courses offered by Springboard can, and will definitely help you out.

  • You must be ready to work with new functionalities and bring in a new understanding of the problem statement in question. 
  • You must ensure that the dataset and codes in question, are arranged, scalable, and retrievable, as well as be debugged. 
  • Time management plays a key role while working on training models. 
  • Business and Domain knowledge is the key to succeed and grow.
  • Cleverly choose the right operational architecture for a case.
  • Opt for the best software development practices.
  • Ensure proper scheduling of tasks.  
  • Open to learning new skills, because Artificial Intelligence and Machine Learning are rapidly changing fields. 

Post-reading this article on ‘How to Become a Machine Learning Engineer’, we are pretty sure that you will understand that the future of the digital world is in the hands of Machine Learning engineers. So, why wait? Take Springboard’s Machine Learning Career Track: Become an ML engineer in six months that comes with a 1:1 mentoring-led and project-driven approach- The only AI/ML Program in India with a job guarantee. Apply Now!