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8 Best Career Scopes in AI and ML engineering

The world is progressing towards new technology. The adaptation rate of new AI and ML technologies are high. Artificial intelligence (AI) hopes to produce some of this century’s most important and revolutionary inventions. The products of the new AI revolution are self-driven vehicles, robot assistance and digital disease diagnostics that will affect how we live and function. And as demand for qualified engineers has more than doubled in recent years, professionals who want to take a lead in research and development in AI are providing endless opportunities. AI & ML engineering will produce an immense amount of career opportunities for the future.

Gartner’s study is expected to clear the way for up to 2.3 million prospects by 2020, according to Artificial Intelligence (AI). And, in the last three years, vacancies in artificial intelligence have duplicated. A related study from Indeed also shows that Machine Learning developers, software technologists, and data scientists play the most demanded role in artificial intelligence.

Amit Ray, a Famous AI Scientist, Author of Compassionate Artificial Intelligence, once quoted, “As more and more artificial intelligence is entering into the world, more and more emotional intelligence must enter into leadership.”

Here is the list of the possible job roles for AI and ML engineering from where they can elevate their knowledge, experience and art of living.

1. Data Scientist:

At present, we are very confident that you grasped the functions and duties of data scientists. They focus on the collection, analysis, interpretation of the data for inferences and observations and the development of successful solutions for market issues. 

Machine learning and artificial intelligence are central components of data science where insight generating approaches are applied from both, regression, predictive analysis and more.

2. Machine Learning Engineer:

Machine learning engineers come with applications, language analysis, statistics, math and more. In the creation and management of self-operating applications that promote machine learning projects, engineers are involved.

A master’s degree in mathematics or computer science is preferable. The requisite technology stacks are Python, R, Scala and Java. The companies are always in demand and their job is rarely empty. They are involved in the fields of identification and speech acknowledgement, theft detection, client insight and risk control. An engineer’s median wage is more than $1000.

3. Research Scientist:

Researchers are working on detailed studies into machine learning and computational intelligence systems. Applicants should hold a PhD or a Master’s Degree in Mathematics or Informatics. 

A research scientist’s salary is very high, and companies are recruiting individuals with a strong AI background. It is quite clear that in the next decade, the value of researchers won’t decrease.

4. Business Intelligence Developer:

The market acumen of the Business Intelligence Developer must be considered in addition to AI. They identify various market patterns by analysing large data sets. The work pays well, and the market for it isn ‘t going anywhere anytime soon. 

A formal bachelor’s degree in computer science, mathematics, or engineering will help you find work. The candidates’ problem-solving skills and intellectual ability should be excellent.

5. AI Data Analyst:

You must have a bachelor of arts in mathematics or computer science to become an IA data analyst. Detailed knowledge of regression and the ability to use MS Excel is important.

The pay for an AI data analyst is relatively poor compared to other AI positions. There is a very steady demand for AI data analysts, but their future cannot be determined.

6. Big data engineering:

A Big Data Engineer’s job is to build an environment that allows business processes to communicate effectively. The role is ideal for those who enjoy experimenting with modern technological tools. To develop a career in AI, you’ll need to learn programming languages like Python, R, and Java.

The pay for an AI data analyst is relatively poor compared to other AI positions. There is a very steady demand for AI data analysts, but their future cannot be determined.

As opposed to other AI jobs, becoming a big data engineer would pay well. Applicants with a PhD in Computer Science or Mathematics are given higher priority for the position. It is self-evident that becoming a Big data engineer will help one advance in one career.

7. Robotics Scientist:

The advent of robots in the area of AI would effectively reduce work. Conversely, employment will also grow as robotics scientists actively strive to programme their robots from major industries. The robots are used to effectively perform such functions.

The applicant should have a Master in Robotics, Computing or Engineering degree. A robotics scientist’s median wage is very high. While robots prefer automation, some skilled builders should be involved. This minimises the possibility of work cuts.

8. AI engineer:

AI engineers are problem solvers who create, test and implement various Artificial Intelligence models. A bachelor’s or master’s degree in data science, computer science, or statistics is required.

Programming skills in languages such as Python, R, or C++ are required. Because of the increasing need for AI engineers, the pay scale is very good.

Starting personal tasks is an excellent way to bring these talents to the test — and to learn new ones. Don’t be intimidated if these criteria sound overwhelming at first. Artificial intelligence is a mansion with several spaces, and gaining the skills and specialisations needed to succeed will take time and maturity. Rather than anything, prospective careers would necessitate a desire to be interested and take risks.