With every organization/business digitizing its operations and taking the lead in artificial intelligence, data science tools, and machine learning, the demand for professionals in their domain is always high. Furthermore, machine learning engineers are in the highest demand because machine learning is an essential aspect of all organizations' automation tools.

As per Brandon Purell, Senior Analyst at Forrester Research, "100%of any company's future success depends on adopting the new technology wetaher its machine learning, artificial intellengence or data science. For companies to be outstanding in the age of the customer driven era, they need to anticipate in well advance what their customers want, and for that machine learning is absolutely essential."

Let us now understand why the demand for a machine learning engineer is more than ever.

What does a Machine Learning engineer exactly do?

A Machine learning engineer works closely with data scientists. In contrast, data scientists extract meaningful insights from several GBs of datasets and communicate these insights to stakeholders for further action. While Machine learning scientists make sure that the models/ simulation used by data scientists can analyze large amounts of data in real-time to get accurate and structured results from the exercise. When these two domains work together, they create technologies for companies that were once considered impractical and impossible. 

As a result, ML Engineers are paving the future of the tech world by enabling several industries to leverage disruptive technologies.

Also, the applications created by data scientists are challenging for software engineers to understand. They are very complex and have no design pattern to understand them for the purpose they are building them. And that is why companies are looking to hire machine learning engineers who can put both skill sets to work. A sound ML engineer in this day and age should be to understand the data scientist's code and make it more accessible. 

What are the duties of a Machine Learning engineer:

Technically a machine learning engineer's work is similar to a data scientist's role, both work with massive datasets. Hence, an ML Engineer should have excellent data management skills. In addition, their job roles require them to combine the rules of data science with programming to help companies leverage their business over others using AI and machine learning technologies.

What are the necessary skills for a Machine Learning engineer:

Broadly we can classify the skill set into three parts as follows-

Soft skills – These non-technical skills help an engineer keep up with the dynamic nature of machine learning. In addition, an engineer must know efficient time management and possess business knowledge for fast ideations.

Technical Skills – Basic technical skills like intermediate-level Python and C++ and basic mathematics concepts like linear algebra, calculus, and statistics are requirements that companies look for while hiring.

Machine learning & neural networks – Machine learning and neural networks are essential skills to find accurate solutions for business problems. However, as machine learning extends beyond neural networks, knowledge of non-neural network concepts like algorithms is a bonus.

So based on this, we can clearly say that Machine Learning will be a sought area, and the job of machine learning will always be in demand.