Some of you reading this article may be thinking, “I want to be an AI engineer, but I’m worried because I hear it’s difficult.”
Certainly, many people may have the impression that AI engineers are difficult because they require knowledge of mathematics and high expertise in AI. However, AI engineers are now attracting attention worldwide, and it is a profession that will continue to grow in demand in the future.
Therefore, in this article, we will explain six reasons why it is said that “AI engineers are difficult”, the characteristics of suitable people, and the steps to become an AI engineer.
 What is an AI engineer?
An AI engineer is an engineer specializing in AI who designs and builds machine learning systems.
An AI engineer’s job is to give various data to AI, process it, and educate AI, and the ability to design ” machine learning ” efficiently is required.
In addition, the programming language ” Python ” is most used for machine learning, and many AI engineers use Python to develop and update AI.
Differences with Data Scientists
There is a ” data scientist ” as a profession that is difficult to distinguish from AI engineers .
A data scientist is a profession that solves problems based on data in various decision-making aspects. While AI engineers design and build machine learning systems, data scientists use machine learning systems to analyze data and solve client issues.
To become a data scientist, you need knowledge of statistics, programming, and machine learning. In addition to technical aspects, a wide range of knowledge such as business and market trends is required.
Difference from SE
Another occupation that is difficult to distinguish among engineers is “SE (system engineer)”. Although they belong to the same IT engineer, the job content and required skills are different.
SEs are mainly responsible for the process of system development, from interviewing clients to defining requirements, designing, and creating specifications.
The ability to design the entire system based on an understanding of the technical aspects is required.
Six reasons why AI engineers are said to be difficult
AI engineers are said to be difficult to become because they require a wide range of knowledge and a high level of expertise in AI. What are the specific difficulties?
There are six reasons why AI engineers are said to be difficult.
- Because it requires logical thinking
- Because technology evolves quickly
- I have a lot of knowledge for my work
- Because the concept of AI is complicated
- Because you need math and science skills
- Client presentation skills required
I will explain each.
1. Because you need logical thinking
If you want to be an AI engineer, logical thinking is an essential skill.
AI engineers often handle data, and when collecting and analyzing, they are required to have the ability to break down the necessary work and methods in detail and execute them.
Therefore, it is a good idea to get into the habit of thinking logically on a daily basis.
2. Technological evolution is fast
AI-related technology trends change day by day.
AI is highly specialized and the technology is constantly advancing, so it is necessary to keep up with the latest information. Therefore, it is difficult to work as an AI engineer unless you are motivated to learn.
The reality is that many people are unable to keep up with these changes and are frustrated.
3. Because there is a lot of knowledge necessary for work
AI engineers are required to have a very wide range of knowledge.
For example, machine learning /deep learning, programming skills, knowledge of related libraries. Knowledge of database operations, data analysis, and advanced mathematics such as statistics.
It is imperative that you keep this knowledge firmly in place.
4. Because the concept of AI is complicated
The complexity of AI concepts makes it difficult to become an AI engineer.
There is no problem in considering AI as “a computer with human-like intelligence”, but the current situation is that the concept of AI is not clearly defined.
Such ambiguity makes it difficult to deepen our understanding of AI. Even if you can understand the basics, you need deep knowledge to acquire the technology to develop AI.
5. Because you need a background in science and mathematics
AI engineers also need mathematics to analyze information mathematically.
Complex machine learning algorithms for AI are based on formulas, and advanced mathematical knowledge such as calculus, linear algebra, and probability statistics is essential to understand them .
Therefore, it is important to acquire specialized knowledge such as data science and statistics at a vocational school with a department or major specializing in AI, or at a science university.
6. Because you need presentation skills to clients
AIÂ engineers sometimes make presentations to clients.
Clients do not have knowledge about AI, so they are required to be able to convey difficult content in an easy-to-understand manner in order to be understood.
However, it is difficult to verbalize and convey complex content about AI, so this is also a factor that is said to be difficult for AI engineers.
AI engineers have a high degree of difficulty, so their annual income is also high
AI engineers are more difficult than other IT-related engineering jobs, so the annual salary is set high in proportion to the difficulty.
The range of skills required is wide, and advanced knowledge and know-how are required, so the current situation is that supply cannot keep up with demand.
Now, I will introduce how high the salary is actually based on “average annual income by age group” and “actual job offers”.
Average Annual Income of AI Engineers by Age
| age | annual income | monthly salary |
| 20-24 years old | 5.7 million yen | 360,000 yen |
| 25-29 years old | 6,600,000 yen to 7,100,000 yen | 440,000 yen |
| 30-34 years old | 6.8 million to 7.8 million yen | 490,000 yen |
| 35-39 years old | 7,860,000 yen to 8,900,000 yen | 560,000 yen |
| 40-44 years old | 8.79 million yen to 10 million yen | 630,000 yen |
| 45-49 years old | 9,980,000 yen to 11,200,000 yen | 700,000 yen |
| 50-54 years old | 10.9 million yen to 12 million yen | 750,000 yen |
| 55-59 years old | 10.8 million yen to 11.9 million yen | 740,000 yen |
| 60-65 years old | 7.1 million yen to 11.9 million yen | 510,000 yen |
The average annual income for all occupations in 2020 was 4.36 million yen.
On the other hand, the average annual income of AI engineers in the previous generation was 7.52 million yen, which is about 1.7 times (3.16 million yen) higher than the average annual income of all occupations.
AI engineer recruitment example
| Company name | annual income |
| Kakaku.com, Inc. | 5 million to 10 million yen |
| recruit | 5.8 million yen to 12 million yen |
| AI Medical Service Co., Ltd. | 5 million to 7 million yen |
| DeNA Co., Ltd. | 3,400,000 yen to 15,000,000 yen |
| Global robot business | Average 7.5 million yen |
| Geekly Co., Ltd. | Average 7 million yen |
| Enigmo Inc. | Average annual income 7.5 million yen |
| Recruit Technologies Co., Ltd. | Average annual income of 9 million yen |
| Next Engineering Co., Ltd. | Average annual income 7 million yen |
Looking at job openings for AI engineers, there are many companies that set annual income of 5 million yen or more even for new graduates.
In recent years, with the increase in demand for AI engineers, the annual income continues to rise.
Characteristics of people suitable for AI engineers
By knowing the personality and aptitude of people who are suitable for AI engineers, it will be helpful to think about whether AI engineers are suitable for you .
The characteristics of people who are suitable for AI engineers are as follows.
- Logical thinker
- People who like to learn cutting-edge technology
- People who want to create new value
I will explain each.
Logical thinker
People who are suitable for AI engineers are those who have the ability to think logically.
Logical thinking is an essential skill for understanding data structures and basic algorithms. It also helps when working with mathematics and statistics.
Therefore, if you have the ability to think logically, you can respond flexibly to your work and grow quickly.
People who like to learn cutting-edge technology
People who are suitable for AI engineers are those who like to learn cutting-edge technology.
AI-related technology trends change day by day. It’s always exciting to learn about cutting-edge technology because progress is always there.
For this reason, it can be said that AI engineers are suitable for people who are always thinking about new AI and business models and want to pursue cutting-edge technology.
People who want to create new value
People who want to create new value are suitable for AI engineers.
Since AI is still in the development stage, depending on its ability, it is possible to create new value by itself that does not yet exist in the world.
In AI development, it is necessary to always think about how to make things better. It is suitable for those who can translate such thinking into the real world.
4 steps required to become an AI engineer
So what steps should I take to become an AI engineer?
The steps required to become an AI engineer are:
- Learn programming languages ​​that can be used for AI development
- Learn programming languages ​​that can be used for AI development
- put together a portfolio
- Search for a job or change jobs based on your portfolio
I will explain each.
1. Learn programming languages ​​for AI development
To become an AI engineer, you need to learn the programming language used in your work.
There are various programming languages ​​used in the work of AI engineers, but Python is the most used. Python is one of the hottest and most popular languages ​​right now.
The secret to its popularity is the use of Python in AI-related development and machine learning, which is one of the keys to promoting DX.
2. Create an original application
After learning a programming language, the next step is to create your own original application. Just learning a programming language does not lead to practical work.
Therefore, we recommend starting with something simple to improve your practical skills.
Just wanting to develop an app won’t last, so let’s have an image of the app you want to create.
On top of that, it will be easier to develop if you document the customer experience, flow line design, and how to hold data that the app realizes.
3. Put together a portfolio
Once you’ve created a few applications, it’s time to put together a portfolio. A portfolio is a way to showcase your achievements and abilities.
If you are an experienced engineer, you can ask the company to measure your level as an engineer by talking about what projects you have participated in and what apps and services you have created.
However, inexperienced engineers do not have practical experience, so it is difficult to judge their level and understanding of programming just by talking.
Examples include “publish the app”, “publish the source code on GitHub”, and “run a technical blog”.
4. Search for a job or change jobs based on your portfolio
Finally, once your portfolio is complete, search for jobs that match your skills and requirements.
The content of your portfolio has a lot to do with your success in finding a job or changing jobs. The more content you have, the more likely it is that people will be interested in your company.
Therefore, prepare a better portfolio and make the most of it as a material to showcase your skills and vitality.
Points to avoid frustration in AI engineer learning
If you have decided to become an AI engineer, you will want to continue learning without getting frustrated. So how do you avoid setbacks?
The points to avoid frustration in AI engineer learning are as follows.
- Create an environment where people can hear
- Be prepared for a high degree of difficulty and difficulty in continuing
- Make a purpose to become an AI engineer
I will explain each.
Create an environment where people can hear
If AI engineers learn by themselves, they may spend a long time making errors that can be solved in a few seconds by asking someone. Such time is very wasteful.
Also, the possibility of frustration increases due to the fact that learning does not progress as expected. Therefore, if you create an environment where you can listen to others, you can study efficiently without worrying about setbacks.
Here are four examples of how to create an environment where people can listen.
- Take advantage of programming school
- Go to a study group
- Participate to the event
- Borrowing the power of an engineer acquaintance
We recommend that you put yourself in such an environment and enjoy learning with your friends.
Be prepared for a high degree of difficulty and difficulty in continuing
There is no doubt that AI engineers are more difficult than other IT-related engineering jobs.
The range of skills required is wide, and advanced knowledge and know-how are required. Therefore, once you have decided to become an AI engineer, you need to be prepared to keep your motivation to learn.
The skills required for an AI engineer include:
- AI development programming
- Mathematical knowledge
- Data analysis
- Machine learning algorithms and deep learning
Try it out and see if it interests you.
Make a purpose to become an AI engineer
If you have decided to become an AI engineer, make a clear goal to avoid frustration.
If you don’t create a purpose, you won’t know what direction you’re going or what you’re doing now. Conversely, by creating a goal, you can clarify what you need to do now to achieve your goal, and you can proceed with your studies without losing sight of the direction you should take.
Skills such as programming are just a means to an end. Create a goal you want to achieve as an AI engineer. Once you have a purpose, you can clarify it further by thinking about the reasons for that purpose.
The future of AI engineers
In conclusion, the future of AI engineers is bright.
AI is now becoming commonplace as a means of doing business in an advantageous manner. Leverage AI to streamline operations and maximize profits.
According to a survey by the Ministry of Economy , Trade and Industry , there is a shortage of about 44,000 people in the gap between the supply and demand of AI human resources in Japan (supply-demand gap). is predicted.
With the expansion of the AI ​​market, it is said that the demand for AI engineers will continue to grow in the future.
Summary
In this article, we have explained six reasons why it is said to be difficult, the characteristics of suitable people, and the steps to become an AI engineer.
AI engineers are a profession that is attracting worldwide attention and is in high demand.
The average annual income is more than 1.5 times higher than the average annual income of all occupations in Japan, and it is possible to receive an annual income of 10 million yen or more, so it can be said that it is a very dream job.
