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Why people say “Don’t be an AI engineer”? 7 reasons you should know!

AI engineer

An AI engineer who has been attracting attention for a long time. However, people keep telling me to stop being an AI engineer.

As an engineer who handles AI, it is attracting attention and demand is increasing, but there is no end to the voices that it should be stopped.

So, why on earth is it said to stop being an AI engineer?

In this article, we introduce people who are suitable / not suitable for AI engineers, and the process to become an AI engineer, based on 7 reasons why AI engineers are said to stop.

Table of Contents 

  • Outline of AI Engineer
  • 7 Reasons Why You Should Stop Being an AI Engineer
    • ① Harder work than other occupations
    • ② Knowledge of difficult mathematics is required
    • ③ I have to study the latest technology every day.
    • (4) High hurdles for technology to be acquired
    • ⑤ Surrounding level is too high
    • ⑥ Tend to lack exercise
    • ⑦ It will be difficult to enter the AI ​​engineer field in the future
  • “Don’t be an AI engineer” doesn’t know the gap between reality and ideal
    • Specific Job Details for AI Engineers
    • Annual income of AI engineers
  • A story about quitting being an AI engineer
  • Should AI Engineers Really Quit?
    • 4 characteristics of people who are suitable for AI engineers
    • 4 characteristics of people who are not suitable for AI engineers
  • Demand for AI engineers
    • Demand for AI is growing in many industries
    • Industries in high demand
  • Situations where engineers work
    • Private enterprises
    • Research institutes such as universities
  • AI engineers are honestly difficult
    • High skill required
  • The Future and Future of AI Engineers
  • How to become an AI engineer
    • Go to college
    • Go to a junior college or vocational school
    • Go to engineering school
    • Learn by yourself
  • Summary

Outline of AI Engineer

AI engineers can be broadly divided into machine learning engineers and data scientists.

A machine learning engineer’s job is mainly to create AI models. We will build an AI model by selecting an appropriate learning model such as deep learning or machine learning for the customer’s problem.

On the other hand, a data scientist’s main job is to analyze a large amount of data using AI technology and approach various issues from the analysis results.

In addition, AI engineers are one of the most popular occupations around the world because of the high demand and high annual income.

Created by the AINOW editorial department I’ve heard of deep learning, but I think there are few people who fully understand it. AI, machine learning, and other words are all over the place, and it’s hard to understand. I don’t know what you can actually use it for and if it works…

7 Reasons Why You Should Stop Being an AI Engineer

So why is it said to stop aiming for a popular AI engineer with high demand? Here are 7 reasons why.

  • Harder than other occupations
  • Requires knowledge of difficult mathematics
  • I have to study the latest technology every day
  • The technical hurdles to acquire are high
  • Surrounding level too high
  • Lack of exercise
  • It will be difficult to enter AI engineers in the future

① Harder work than other occupations

The first is that it is more demanding than other occupations.

While AI engineers are a profession with high demand, the required technical level is high, and in addition, the number of AI engineers supplied to the IT market is small, making it a tough job.

In addition, there are many changes in system specifications, and in order to meet client deadlines, there are many overtime hours and holidays.

Because it is hard work, the treatment is good, and there are cases where you can work even if you have no experience, but you also need to consider work-life balance.

② Knowledge of difficult mathematics is required

Second, it requires knowledge of difficult mathematics.

Unlike other engineers, AI engineers are also required to have knowledge of mathematics. In particular, statistics, calculus, and linear algebra are frequently used. Most of these are the contents to be learned at university, so it will be necessary for people with liberal arts to be prepared to become AI engineers.

③ I have to study the latest technology every day.

The third is that you have to study the latest technology every day.

In addition to supporting frequently updated programming languages ​​and learning a wide range of fields such as machine learning, deep learning, and mathematics, it also supports the latest technologies such as rapidly developing AI. I have to go.

You will need to constantly check the latest information and learn new things, so you will need a lot of study time outside of work hours.

(4) High hurdles for technology to be acquired

The fourth is that the technical hurdles to acquire are high.

Due to the high demand for AI engineers, many people try to change jobs from inexperienced people and engineers. However, the current situation is that the rate of frustration due to too high hurdles is high.

There is a possibility that you will be hired without experience, but some people will be frustrated because of the large amount of work as an engineer.

⑤ Surrounding level is too high

The fifth is that the surrounding level is too high.

Many AI engineers have learned the latest AI programming technology at universities and graduate schools, and the percentage will continue to increase in the future.

Therefore, if you aim to become an AI engineer from inexperienced, you have to compete with high-level aspirants for the hiring frame.

In order to differentiate yourself from those around you, it is necessary to devise ways such as acquiring the skills to make business-side proposals by making use of your past experience.

⑥ Tend to lack exercise

The sixth is that it tends to be lack of exercise.

AI engineers work long hours in front of a computer. Therefore, it can be said that it is an unsuitable job for those who find it painful to sit for a long time.

Lack of exercise can also lead to illness. Also, staring at a computer for long periods of time can lead to health problems, such as eyestrain.

⑦ It will be difficult to enter the AI ​​engineer field in the future

The seventh is that it may become difficult to enter AI engineers in the future.

Nowadays, more and more people are learning programming from elementary school. Therefore, many of the people who will become AI engineers in the future will be involved in IT from an early stage, such as learning programming from elementary school.

As you have been programming for a long time, your programming skills and IT knowledge will increase.

Therefore, it will be more difficult to become an AI engineer in the future by competing with people who have been educated from a young age, compared to the present where you can work as an AI engineer if you study hard.

“Don’t be an AI engineer” doesn’t know the gap between reality and ideal

One of the reasons why it is said that “AI engineers should stop” is because there is a big gap between the reality and the ideal of AI engineers. As a result, you may be shocked that you cannot do the work you thought you would, and you may quit your job.

In order to fill such a gap, it is important to understand the correct job content and annual income of AI engineers.

Specific Job Details for AI Engineers

The job of an AI engineer is to give data to the machine, mainly using technologies such as machine learning and deep learning, and let it learn how to make decisions and ways of thinking. This creates an AI.

In addition, the content of the AI ​​engineer’s work is roughly divided into six categories: “planning”, “AI system development”, “data preparation”, “AI learning”, “testing and evaluation”, and “research and investigation of the latest technology”. .

AI engineers have many tasks, and each task requires different knowledge and skills.

Annual income of AI engineers

Here are the annual salaries of AI engineers.

The Ministry of Health, Labor and Welfare’s 2021 Wage Structure Basic Statistical Survey shows the following.

  • Length of service: 10.5 years
  • Working hours/month: 167 hours/month
  • Overtime: 13 hours/month
  • Monthly salary: 353,300 yen
  • Annual bonus: 990,100 yen
  • Average annual income: 5,229,700 yen

Looking at the statistical data of recruitment service companies, we can see that the average annual income of AI engineers is in the 5 million to 8 million yen range.

A story about quitting being an AI engineer

I will introduce the experiences of people who actually experienced AI engineers.

In the end, it is a real problem that must be solved, not a machine learning problem. There is no need to use AI ( machine learning ).

For employment, AI engineers are required to have a master’s degree or higher in information technology.

My frank impression after trying AutoML Tables is only one point, “Oh, I can’t beat machines like me.” I admit that I’m not an expert and I’m not actually working on it, but I’ve realized that since I can’t beat machines, I’ll never have a chance to work in the machine learning business again.

As described above, there are not many jobs that utilize AI, the level of the surroundings is too high, and the appearance of AutoML Table, which allows anyone to use data analysis using machine learning models, will take away jobs. A variety of hardships can be seen from the experiences.

Should AI Engineers Really Quit?

It is hard to say whether AI engineers should really quit. People have pros and cons for work.

4 Characteristics of people who are suitable for AI engineers

I will introduce four main characteristics of people who are suitable for AI engineers.

  1. Have the ability to think logically
  2. I like to write code
  3. Ambitious
  4. I like math

(1) Have the ability to think logically

First of all, I am a person with logical thinking.

AI engineers have many situations where logical thinking is required. In particular, the ability to think logically will be useful when thinking about programming and algorithms.

②I like to write code

People who like to write code are also suitable for AI engineers.

In programming, we write the code of the program based on the design document of the system. Programming is an essential skill for AI engineers, and most coding tasks, including error resolution, require a great deal of time.

Therefore, if you like writing code, it will be less painful.

③ Strong desire to improve

And I am a person with a strong desire to improve.

In the fields of AI and IT handled by AI engineers, new technologies are being built and developed every day.

Since it is necessary to study ever-evolving technology and adapt to the updated programming language, it is said that AI engineers are better suited to those who are highly motivated than those who are not interested and do not want to improve their skills. I can say

④ I like mathematics

Finally, I am a person who likes mathematics.

As mentioned above, AI engineers need knowledge of mathematics. People who are not good at mathematics or who barely touched mathematics at university may have a hard time if they become AI engineers.

4 characteristics of people who are not suitable for AI engineers

Next, I will introduce four characteristics of people who are not suitable for AI engineers.

  1. I think it’s because it’s a trendy job
  2. I want to become an engineer and have fun and earn money
  3. I hate math
  4. no ambition

① I think it’s because it’s a trendy job

First, there are those who aim to become AI engineers simply because it is a job that is trending right now.

Currently, AI engineers are one of the occupations with high demand and are popular because there are many recruits even if they have no experience, but the skills and work content required for AI engineers are difficult and difficult.

It would be a good idea to learn the knowledge that AI engineers actually need, such as natural language, and then aim for it.

② I want to become an engineer and have fun and earn money

Second, people who want to have fun and make money.

AI engineers earn a good annual income, and many people think that they can easily earn money with a comfortable desk job.

But this idea is wrong.

AI engineers often work on personal computers, but AI engineers have various jobs, and as mentioned above, they are considered to be hard work.

Therefore, if you want to take it easy and earn money, you may want to consider other occupations.

③I hate mathematics

And I hate math.

Knowledge of mathematics is essential for AI engineers. Knowledge of statistics, calculus, linear algebra, and possibly algorithms is essential. So it might be a tough job for people who don’t like math.

④ No ambition

Finally, people who are not ambitious.

As I have told you so far, new technologies are being built and developed every day in the AI ​​and IT fields handled by AI engineers. Therefore, it can be said that people with a strong desire to improve are more suitable for AI engineers.

Demand for AI engineers

AI engineers are currently in high demand. Here’s why.

Demand for AI is growing in many industries

The reason why the demand for AI engineers is increasing is that the demand for AI is increasing in many industries and fields.

It is active not only in the IT industry, which is generally imagined, but also in a wide range of fields such as agriculture, medicine, construction, and finance. Many people are.

Industries in high demand

Two industries that are in particularly high demand are:

System development

The first is system development.

In recent years, AI-based systems have been used in all aspects of society, and have gradually penetrated our daily lives, such as voice recognition, online chatbots, recommendation engines (AI algorithms), and AI-driven automated stock trading. I’m getting started.

Companies are also shifting to DX, and efforts are being made to utilize data and reduce operations through AI.

Product development and research

The second is product development and research.

In conventional material development, we first made a hypothesis, selected materials, and repeated simulations, synthesis, and evaluations until a compound that met the purpose was created.

However, in recent years, AI has become able to replace the process of searching and selecting compounds. Until now, the probability of finding a useful compound was 1 in 100,000, even though it took a long time and a lot of effort, but by using AI, the probability has been increased to 1 in 100.

In this way, AI is being widely used in various industries, and the demand for AI engineers involved in AI is also increasing.

Situations where engineers work

We will introduce two situations in which AI engineers are actually active.

  • Private enterprises
  • Research institutes such as universities

Private enterprises

The first is a private company.

AI engineers work at a variety of companies, including IT companies, automobile manufacturers, and electrical manufacturers.

My job at a private company includes analyzing data within the company and understanding customer needs.

Understanding customer needs is important for any company, as it is necessary for developing new products and brushing up existing products.

In this way, AI engineers can contribute to solving the problems that companies have, so major companies are actively hiring AI engineers.

Research institutes such as universities

The other is research institutes such as universities.

If you want to be an AI engineer because you want to develop the AI ​​field or work in a cutting-edge field, working at a research institute is a good idea.

At research institutes, you can work on development of the AI ​​field rather than development using AI.

AI engineers are honestly difficult

However, it can be said that it is honestly quite difficult to become an AI engineer. This is because, as we have introduced so far, AI engineers require advanced skills.

High skill required

The skills possessed by AI engineers require more advanced knowledge and abilities than engineers who perform normal programming.

In addition to various specialized knowledge such as what kind of learning model to use, data selection for learning, and parameter adjustment, knowledge of mathematics and statistics, programming ability, and logical thinking are also required.

The Future and Future of AI Engineers

According to the results of a survey by Fuji Chimera Research Institute, the domestic market for the AI ​​business, which was 500 billion yen in 2018, is expected to grow significantly to 2.1 trillion yen in 2030.

In addition, the spread of AI technology is expected in the financial, manufacturing, and medical and nursing care industries.

Among them, the demand for AI engineers will increase.

How to become an AI engineer

So what should I do to become an AI engineer? There are many ways to do this, but here are four.

Go to college

First, one is to study AI at university.

Recently, there are cases where science and mathematics departments at universities have departments related to AI. Some faculties are conducting cutting-edge research on AI, so it can be said that it is a shortcut to becoming an AI engineer.

On the other hand, the disadvantage is that it is very difficult for people who are currently working as a member of society to go to university.

Therefore, studying at university is recommended for students.

Go to a junior college or vocational school

The second method is to study at a junior college or vocational school.

What makes junior colleges and vocational schools different from universities is that you can complete your studies in two years. If you are a student and want to build a career as an engineer from an early stage, or if it is difficult to go to university financially but want to study hard at school, you should study at a junior college or vocational school.

Go to engineering school

The third is to go to an engineering school and study.

There are various schools, so you can find a classroom that suits your purpose and convenience.

At engineering schools, the number of classrooms that can be taken online is increasing, and it is recommended for those who want to become an AI engineer while working.

Learn by yourself

And the fourth method is self-study.

The advantage of self-studying is that it costs nothing and you can learn at your own pace.

On the other hand, it takes time to learn because there is no one to ask casually when there is a part that you do not understand. There is a disadvantage that it is not suitable for those who do not know how to study in the first place.

However, if you want to be an engineer while working and know how and what you want to learn, you can study by yourself.

Summary

In this article, I introduced the reason why AI engineers are said to “stop” because of their work and annual income, and introduced what to do to become an AI engineer.

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