Neural networks have only recently become commonplace, and while debates about the prospects of AI continue, a neural network specialist is already a sought-after profession. Find out what these specialists do, how to learn to work with artificial intelligence, what the professional prospects are, and the salary level in this field in the article.
Neural Network Specialist: Who Are They
Actually, a neural network specialist is a general term for many professions, and each job encompasses its own set of tasks:
- Programmer or developer. Their role involves creating the network itself, to be used in a particular field. Hence, there will be specific requirements for AI. For such work, a programmer needs knowledge of Python, expertise in working with libraries like PyTorch and TensorFlow, operating systems like Linux, and understanding the types of in-demand neural network architectures.
- Machine learning specialist. To ensure neural networks operate correctly, they must be taught using special methods. This requires knowledge of several programming languages, proficiency in the pertinent tools, and strong mathematical abilities.
- Data engineer, analyst, or data architect. Programmers and technical specialists tasked with preparing data needed for neural networks to function.
- Deep Learning engineer. This professional deals with deep learning algorithms, system architecture, code transformation, and setting up cloud infrastructure – all necessary for creating complete production models. This profession is considered the most complex.
- Deployment Engineer. This is the person responsible for deploying models, i.e., placing the finished product on servers, testing system operation, troubleshooting, and so on. In addition to programming languages, proficiency in working with cloud platforms, containerization technologies, and scripting languages is also required.
- Computer vision developer. As the title suggests, this employee is involved in working with visual content.
- NLP Engineer. Specializing in the processing of written or spoken language used to train AI. Their efforts determine the success and feasibility of user interaction with services like ChatGPT, online translators, or basic chatbots.
- Ethics specialist. Moral and ethical principles are important even for artificial intelligence, especially if the neural network learns independently using data from the internet.
- Integrated circuit developer or microelectronics engineer. Arguably the most complex and purely “technical” job, but fundamental. No AI chip – no network at all.
How to Enter the Profession
Regardless of the specialty you choose, education is necessary. Where? Currently, there are three options:
- Self-education. Perhaps only in the IT sector can self-taught individuals be “better” than university graduates. Not always, but practice shows that talented autodidacts achieve significant success. However, to reach the necessary level, far greater effort than institutional education is needed, including developing a personal learning system. Self-discipline, determination, and effective time management are all critical for self-study.
- University. A reliable choice for those wishing to learn a profession from scratch. However, modern programs do not always offer what is needed. Nonetheless, learning programming languages and acquiring the necessary skills is possible. Among the advantages are the diploma confirming qualifications. The downside is that university curricula may not always meet contemporary standards. Which universities can train AI engineers? The Bauman Moscow State Technical University program regularly ranks within the top best not only in Moscow but countrywide. The Moscow State University also offers an educational program for all its postgraduate students.
- Online courses, both paid and free. An ideal option for those who are already familiar with neural networks but lack proper training. With a sound choice of course, it is possible to obtain a full range of knowledge and skills quickly and affordably. You can maintain your main studies or job without interruption.
Career Prospects
Before purchasing and completing a “Neural Network Specialist” course, it’s crucial to understand what to expect for a newly minted engineer or programmer who creates networks or trains them or works with them on projects. Currently, the profession is in demand – with several hundred vacancies open. In the future, the number of job openings will grow – as AI is increasingly integrated into everyday tasks, more specialists will be needed.
Even now, job vacancies attract many, at least with high salary levels – not only in Moscow but also in other cities across the country. If you are considering how to become a neural network specialist – it’s best to choose the appropriate training course and start today.
Expected Salary
The drive to become a professional in AI is not only based on interest – future earnings are also a significant factor. As of mid-2023, the salary level ranges from 70,000 to 420,000 rubles. Naturally, the highest figures are in Moscow, where programmers and engineers are promised incomes of no less than 115,000 rubles.
It’s difficult to predict salary levels in the future. However, as the country is focused on IT development, incomes will not fall, and the number of vacancies will only increase. Certainly, the prospect of market saturation shouldn’t be ignored, but that won’t happen until there’s an oversupply. And the market is far from saturation – this field is only just starting to develop.
Conclusions
The AI programmer and engineer’s profession is, without exaggeration, the career of the future. Neural networks are quickly developing and being integrated into all spheres of human activity, which is why the profession is highly demanded now and will continue to be in the forthcoming decade.
One can learn this profession independently, but simpler and more efficiently – by completing the relevant course. You can choose a university with a suitable program or an online course. In the latter case, you not only gain knowledge but also benefit from a convenient study schedule without the need to interrupt your main studies or job.
