TAdviser study: Key AI employers in Russia 2024

The TAdviser analytical center conducted a study of approaches to attracting and hiring talents in the field of AI and prepared a rating of key employer companies for AI in Russia.

According to TAdviser, in 2024, 90% of the top 100 largest companies in Russia from different sectors of the economy use machine learning (ML) and artificial intelligence technologies for internal business tasks, or for developing commercial products for the external market. The development of AI initiatives and the involvement of specialists in machine learning and AI technologies is becoming one of the key priorities in the framework of the national project "Data Economics" launched in 2025.

The demand for personnel in the direction of AI is growing against the background of a continuing shortage of qualified IT specialists in the Russian market. Ministry of Digital Development It is estimated at 700 thousand people, Sberbank VTB and it is predicted that this situation will continue until 2030. According to data, over the Superjob past year, the number of vacancies for specialists with experience with neural networks and machine learning skills has tripled.

The demand for AI/ML specialists is growing, but not rapidly, but moderately. Many companies talk about AI, but have not yet taken any big steps in this direction, with the exception of a few major players in the market. There are many AI/ML specialists of the junior level in the labor market, but there are very few senior experts. In our experience, the industry really needs Senior specialists and architects of a high level - now there is a huge demand for them, as companies begin to launch large AI projects and they need professionals who are ready to develop, implement, scale and technical support, - comments Boris Ryzhkov, HR Director Softline Digital (Softline Group of companies).

The increase in interest in AI and machine learning professionals is due to the expansion of projects in automation, big data and analytics, but the pace of hiring varies across sectors. The dynamics in our company is stable: we continue to actively search for and attract experts for projects on automation of production, digitalization of business processes and are faced with competition for strong candidates, especially with companies that offer relocation. We see that the demand for specialists who combine AI competencies with skills in product development and integration is increasing, - said the representative of Severstal.

The dynamics of growth is especially noticeable in the last two years. This is partly due to the advent of ChatGPT in 2022. However, not only large language models (LLM), but also all areas of AI technologies are developing dynamically, and at the same time, the interest of specialists in the industry is growing. There are now many junior-level applicants on the market (juniors and beginners) and competition among them is quite high. At the same time, there are much fewer confident middle (medium level of knowledge) and senior (more experienced applicant), - comments Marina Kvasova, HR Business partner MTS AI.

The growth in the number of new vacancies is currently outpacing the growth in the number of high-quality personnel. There are more and more good ML specialists, but the number of developments in the field of AI is growing faster. This is a general trend for the market and for VK in particular. The higher the level, the more difficult it is to find an employee, - comments Ekaterina Ivanova, HR Director of Technical Functions of VK.

For the tasks of various AI projects and the development of product development for AI, highly qualified data scientists (Data Scientists, DS), ML engineers, MLOps and DevOps engineers are in demand.

Specialists in the field of machine learning, natural language processing, computer vision and deep learning are most in demand. The demand for DS specialists is increasing. The most frequent request is for specialists with experience, but since they are not enough, the business as a whole is ready to raise specialists for itself, including by training interns, - comments Sergey Karpovich, deputy head of the AI T1.

First of all, data scientists working at the interface of data analysis and building machine learning models, Phyton developers and QA engineers are in demand, - said Victoria Trifonova, HR director of the cloud and AI technology provider Cloud.ru.

At Lamoda Tech, we have been successfully implementing data-based solutions using machine learning technologies for more than five years and have seen a constant increase in demand for specialists in this area - ML engineers, data scientists, backend engineers and product managers of ML products. Confident middles, signors and team leaders are most in demand. Recently, competition for experienced specialists has intensified, including due to the outflow of professionals abroad, - said Alexander Zhelubenkov, Head of Data Science, Lamoda Tech.

The main demand is focused on middle and senior ML engineers with experience in building and optimizing models, as well as Data Scientists, who can work with large amounts of data. Specialists who are able to apply their knowledge to the development of applied products are in particular demand - from recommendation systems to image processing and NLP. Not only technical skills are important, but also an understanding of business goals, which allows you to integrate AI into products, improving the user experience, - noted in Severstal.

Russian organizations developing using AI technologies have been increasing the number of vacancies in this area in recent years.

MTS AI is actively expanding ML teams, AI researchers, AI coaches. New specialists and vacancies also appear, for example, industrial engineer, RAG engineer, etc., - explains Marina Kvasova.

On average, according to TAdviser, teams of AI specialists make up about 50-100 people for medium-sized businesses, or dedicated structures (departments or subsidiaries) within large corporations. In a large high-tech business (primarily fintech, e-com or digital), AI teams number 500-1000 people and continue to grow.

As the TAdviser study showed, the largest teams of AI specialists collect banks, retail, e-com, as well as IT developers. The latter are focused on creating finished products and services based on AI and promoting them on the market, including for V2V customers. Banks, retail, e-com and industry tend to develop products internally using AI to meet specific business needs. Although some structures are also considering the subsequent commercialization of such developments.

For example, at T-Bank, AI and machine learning technologies are integrated into the products of an ecosystem of more than 45 million customers - solutions are used both in financial products and in telecommunications and lifestyle services. And to improve the efficiency of internal corporate processes, T-Bank creates piggy banks based on artificial intelligence for all major professions within the company: support, sales, representatives and IT specialists.

We, like many other companies in the market, plan to increase the number of teams that develop AI technologies within the organization. Our company has a separate expertise center that deals with the development and security of AI. Such specialists primarily need certain knowledge in the field of mathematics, knowledge of the frameworks used, algorithms, - comments Vladislav Tushkanov, head of the research and development group of machine learning technologies at Kaspersky Lab.

Kaspersky Lab notes that three main teams are engaged in the use of AI. The Detection Methods Analysis Group team is developing ML algorithms for detecting malware based on both static features and behavior. The Technology Research Department team as part of the Future Technologies department specializes in the study of promising AI technologies, develops the Kaspersky MLAD product, develops the Kaspersky Neuromorphic Platform (KNP), participates in the creation of the next generation neuromorphic processor, provides AIST services for AI security. And the MLTech team is responsible for developing the corporate ML infrastructure for training ML models, creating models for detecting content threats (phishing and spam), as well as introducing AI technologies, including those based on large language models, into enterprise services and solutions (for example, MDR, Kaspersky SIEM (KUMA) and Kaspersky XDR). Other teams also actively use ML to solve many problems - from machine vision technologies in the Kaspersky Antidrone team and studying AI developer assistants in the CoreTech and KasperskyOS departments to applying ML to the search for complex APT attacks in GReAT.

Domestic companies strive to attract talents in an overheated market not only with salaries. Applicants also pay attention to the strength of the brand, the professional environment in the team, the technology stack and development culture, as well as opportunities for self-development.

As the TAdviser study showed, in larger structures, as a rule, career ladders for AI specialists are more developed, competency matrices and grade tracks have been worked out. Most companies provide for both vertical and horizontal growth along the expert branch.

Vertically, employees can grow in stages - from the positions of the head of the group to the head of the department with teams of 40 + employees, in some companies - to the director of the department. Development into an expert thread implies growth to the role of TechLead or an architect.

Given that AI teams are formed as dedicated structures in companies relatively recently, the average work time of AI specialists in one organization is 2-2.5 years, the TAdviser survey showed.

The exception here is companies that began the development of AI expertise earlier. So, Kaspersky Labmachine learning it has been used for almost 20 years. 50% of employees who develop ML work for more than 5 years, and 20% - more than 7 years. Taking into account the specifics of the direction cyber security , the practice of internal transitions is widespread in the company, so a large share of positions are closed by internal candidates, without opening vacancies.

Internal development of specialists is a generally common practice in the IT market, which allows you to reduce the time to find and adapt new employees, as well as reduce the risks associated with possible problems of their integration, or rapid departure.

For internal development purposes, AI employers offer free training within the company - in dedicated centers of corporate universities or academies. Pump both "hard" and "soft" skills, as part of the formation of a culture of continuous education by organizations.

We focus not only on hiring new specialists, but also on developing the competencies of the existing AI team. We invest in training: for example, each employee has an annual budget for paid programs, as well as a wide list of internal courses, we invest in the formation of individual career trajectories. We also support the initiatives of our AI team to actively introduce artificial intelligence technologies into the company's business processes, - comments Victoria Trifonova.

The trend in retraining encourages companies to budget for training. Many of the organizations surveyed by TAdviser support and pay (up to 100%) for employee training at various external programs, as well as attending professional events.

Closing the personnel deficit, companies begin to play long - growing employees, starting from trainee positions and collaborating with universities. Companies interviewed by TAdviser open departments in ML or AI at MIPT, ITMO, HSE. For example, Sberbank now has 17 programs in the IT/DS direction, where 820 students are trained. "Clean" DS is presented in cooperation with HSE, MIPT, ITMO, Innopolis, St. Petersburg State University, MISIS, Skoltech, NSU, UrFU, FEFU, KFU, SNIU, TOGU.

Cooperation with universities helps companies raise the level of graduates "for themselves," recruiting interns who then continue to work in AI teams. To train specialists, joint AI programs are created with different educational institutions. For example, T-Bank cooperates with MIPT (joint master's and research laboratory), HSE (developed a course on recommendation systems) and Central University (bachelor's and master's degree, as well as a research laboratory for students in the areas of AI Alignment, LLM Foundations and Multimodal AI).

Lamoda Tech is preparing a scholarship program for MIPT bachelors in the faculties of FPMI and FRKT, where, among other things, students are trained in the direction of Data Science, and Lamoda Tech employees will act as mentors. Avito plans to start cooperation in the field of fundamental education with 11 key specialized universities by 2028.

We interact with leading technical universities and open educational programs at ITMO, MSTU, HSE, St. Petersburg State University and others: we launch courses annually, there is a bachelor's and master's degree, "says Ekaterina Ivanova.

According to the results of the TAdviser study, the main considered factors of the possibilities of attracting and developing AI specialists became the basis for forming a rating of key AI employers in Russia. Both basic parameters - current hiring, career and training opportunities, and technological - areas of product development were evaluated. The contribution of companies to the construction and development of the Russian AI community was also taken into account.

A local community has already formed in the Russian ML/AI industry, which continues to expand. Various training programs, hackathons and research competitions are gaining great popularity. Large market participants are invested in the development of the professional community: they provide platforms that bring together enthusiasts, pioneers and experts in the field of AI, but there remains an important issue of attracting and training new specialists. It is unpromising to consider further exchange of expertise in isolation from the global market. Here opens a large field for collaborations and cooperation, new initiatives that will allow communities from friendly countries to exchange experiences, which, in turn, will lead to the development of technology. Democratization of AI is not just a trend today, but a young and confident direction that creates new professions and at the same time new opportunities for both business and end users, - notes Victoria Trifonova.

MTS AI employees win international competitions, taking prizes. They conduct mitapes, training programs, work with students and schoolchildren, write A * level articles, continue to develop AI and ML in their field of knowledge. Other market participants are also quite active, since the company should be recognizable in the race for specialists in the labor market, and its own communities help in this, "comments Marina Kvasova.

AI communities enable rapid information sharing. This contributes 100% to the development of technology. So far, there is no such thing that market participants actively unite and create one global community, but strong local communities are formed at the company level, which hold thematic conferences, arrange hackathons, etc., - comments Boris Ryzhkov.

The Russian DS community is now actively accumulating experience and exchanging knowledge. Its development involves both individual companies and large players in the IT conference market, such as Ontiko and Jug, which have launched two new conferences on AI and machine learning, adds Alexander Zhelubenkov.

In August 2024, we conducted a large study of the profession of ML specialists. It described ML's professional community as open and active employees who willingly share experiences and share best practices. We also noted that the community helps to easily adapt Junior professionals. Key employers for ML specialists are increasingly feeling the importance of the profession and the complexity of hiring, - comments Ekaterina Ivanova.

{{quote 'The local community is developing, but its activity is still lagging behind international standards. There are positive dynamics: hackathons, mitapes, conferences initiated by both large corporations and universities are held. Market participants are interested in such initiatives, but so far they do not interact enough with each other. The formation of a more active community will help speed up the exchange of knowledge, improve the qualifications of specialists and stimulate the development of domestic AI products. This is especially true against the background of limited access to some international resources, - summarize in Severstal. }}

Companies participating in the TAdviser rating represent various sectors of the economy, including IT, telecom,, finance, retail e-com and industry. Companies representing large and medium-sized businesses participate in the ranking.

A total of 45 companies were interviewed. The final consolidated rating included 20 key AI employers. The dedicated divisions or subsidiaries of organizations leading the development of AI were compared.

Each TAdviser company receives points in each of the following categories:

1. Career development in ML/AI specialties
2. Development of hard skills by ML/AI
3. ML/AI product development *
4. Participation in ML/AI community/market development
5. Employee Satisfaction

^{* Internal development and product development for the market. Companies commercializing their AI developments get more points}

Each category receives its own score in points, and also has its own weight in the final score.

The data for the rating was provided by representatives of companies. Open source data, previous research data and TAdviser expert assessments were also used for the assessments.