Professionals for Artificial Intelligence

rabiakhatun

In 2023, the demand for "artificial intelligence trainers" increased in Russia - according to HeadHunter, the growth was 130%. Employers posted more than 13 thousand vacancies for AI trainers. One of the first companies in the world to start hiring trainers was OpenAI, the developer of ChatGPT. As magical as the name of the profession sounds, in our country specialists cannot yet boast of high salaries - on average, representatives of this profession receive from 75 thousand to 100 thousand.

Their main task is to help AI learn to create correct, competent, logical and relevant answers to queries.

To do this, it is necessary to content writing service select and prepare training data for AI algorithms, evaluate and edit AI texts – monitor the effectiveness of the model and adjust parameters, control the absence of distortions and biases in the results.



This role requires both AI and machine learning competencies and knowledge of the subject area in which the algorithms will be applied. Such specialists are sought after in fintech. Companies often offer flexible work formats for AI trainers, which allows them to combine work and study. There is an opportunity for financial growth due to an increase in the number of tasks and the quality of work performed.

DATA ENGINEERS FOR AI

Data engineers are responsible for preparing and processing the data needed for artificial intelligence systems to function. Specialists collect, clean, and process data to make it suitable for analysis and training of AI models.

The tasks of AI engineers include:

collection of data from various sources (databases, sensors, expert specifications);
converting data into formats suitable for AI training;
search and correction of errors, omissions and unstructured information;
annotation and labeling of data according to AI tasks;
validation of the quality and volume of data for the correct operation of algorithms.
A data engineering specialist needs the following hard skills. Ability to design and implement complex data processing systems, knowledge of several programming languages ​​(such as Python, Java, Scala), knowledge of orchestrators, cloud and Big Data technologies (Apache Hadoop, Kafka, for example), understanding of the DevOps approach, knowledge of programs such as Ansible, Terraform or Kubernetes. In addition, you need to be able to work in Linux and Git environments. Data engineers should also have an understanding of business processes in which AI will be involved. The average salary of a professional is 400 thousand rubles.

explanation of the principles and logic of AI models to developers and business analysts;
identifying potential errors, failures and biases in AI output;
consulting interested parties on the further application and development of intelligent systems;
assistance in the correct interpretation of AI results and formulation of requirements for future versions.
To successfully fulfill this role, a specialist needs multidisciplinary competencies - an understanding of AI technologies, analytical skills, the ability to clearly explain complex concepts to both technical specialists and a managerial audience without a deep technical background.