When recruiting an AI researcher, experience in conducting advanced research in the field of artificial intelligence is crucial. The candidate should have a history of publications in reputable journals or conferences, which demonstrates deep knowledge and innovative approaches to AI problems.

A thorough knowledge of machine learning theory, including supervised, unsupervised algorithms, and reinforcement learning, is essential. The candidate should demonstrate the ability to design and implement new algorithms and optimise existing methods.

Strong programming skills, especially in languages such as Python or R, are required. Experience with data processing and machine learning libraries such as TensorFlow, PyTorch or Scikit-learn is also important.

A deep knowledge of mathematics and statistics is essential for understanding and developing machine learning models. The candidate should be able to apply advanced statistical and mathematical techniques to analyse data and develop predictive AI models.

It is important that the candidate demonstrates the ability to think critically and solve complex problems. An AI scientist should be able to quickly identify research problems and effectively search for new and original solutions.

The ability to effectively present research results, write scientific reports and articles, and participate in scientific discussions is essential. The candidate should be able to clearly communicate complex ideas and results of their work to both subject matter experts and those not directly involved in AI.