Data Scientist at Wildberries

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Maria Zharova,
The market is already reacting to this trend: many recruiters include the ability to work with neural networks in their candidate requirements. In addition, in recent years, more and more new vacancies for working with artificial intelligence have appeared. Here are some of the most popular:

A Prompt Engineer is a person who understands how to “talk” to AI in order to get the most accurate and useful answers from it. Their job is to formulate requests so that the AI ​​understands what exactly is wanted from it and gives the desired result. For example, a company needs an image to advertise a new product. The Prompt Engineer creates a request and describes the style, color scheme, and composition of the image, and specifies what impression it should make on the client.
An AI trainer helps train artificial intelligence models. They analyze the interaction of the neural network with users, correct shortcomings, and add missing data. For example, a trainer can teach a bosnia and herzegovina telegram data chatbot to correctly process rare requests or suggest how to respond to non-standard questions.
An AI Ethics Specialist develops rules and standards for the safe and fair use of neural networks. For example, such a specialist can check that the algorithm for selecting candidates for vacancies is not biased.
An AI Solutions Architect is a person who develops and implements AI systems into a company’s processes. Their job is to configure AI so that it effectively solves business problems and optimizes employee performance.
The Chief AI Officer is a top manager who is responsible for the implementation of AI in the company's strategies. His task is to determine how the neural network can help the company grow, what technologies should be used, and how to allocate resources.
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From Trainer to Engineer: 6 New IT Professions for Those Who Want to Work with Neural Networks
Quantum AI
Quantum artificial intelligence is a new direction that could significantly change the way we use neural networks.

Unlike traditional computers, which perform calculations sequentially (bit by bit), quantum computers operate on quantum bits (qubits). This allows quantum AI to process multiple solutions to a problem at the same time – and much faster. Such artificial intelligence can help in developing new drugs, forecasting the economy, optimizing logistics, and making scientific discoveries.