The ideal candidates are more than just programmers or data scientists. They are visionaries with a hands-on mentality who are willing to push the boundaries of what's possible. Here are the key qualifications I'm looking for:

• Profound Technical Knowledge: Excellence in machine learning, deep learning, reinforcement learning, computer vision, natural language processing (NLP), and robotics.

• Innovation Capability: The ability to develop new approaches and find creative solutions for complex problems, especially when standard solutions are insufficient.

• Practical Experience: Not just academic knowledge, but also demonstrable experience in implementing AI systems in real-world applications. This means bringing models from conception to production.

• Systems Thinking: The ability to design end-to-end solutions that seamlessly integrate AI models into existing (or new) infrastructures. This also includes an understanding of scalability and maintainability.

• Problem-Solving Orientation: A pragmatic approach to challenges and the ability to make effective decisions under pressure.

• Communication Skills: The ability to clearly and understandably communicate complex technical concepts to non-technical stakeholders.

• Team Player: I'm looking for individuals who thrive in dynamic environments and are willing to share knowledge and learn from each other.

To build a truly powerful AI team, I need a mix of different disciplines. The breadth of knowledge is crucial for tackling the diverse challenges that automation brings:

• Computer Science / Artificial Intelligence: This is the core competency. Experts specializing in Machine Learning, Deep Learning, Computer Vision, NLP, and Reinforcement Learning.

• Robotics / Mechatronics: For physical implementation and interaction with the real world, engineers with expertise in robotics kinematics, sensor technology, actuators, and control systems are indispensable.

• Data Science / Statistics: To understand the vast amounts of data that AI systems need and generate, data scientists with strong statistical knowledge and experience in Big Data technologies are necessary.

• Software Engineering: To develop robust, scalable, and maintainable AI applications, I need experienced software engineers who know and can apply best practices in software development.

• Cognitive Science / Psychology: For the development of user-friendly and intuitive AI systems, especially in the field of human-robot interaction or for empathetic AI systems, an understanding of cognition and human behavior can be of great advantage.

• Mathematics / Applied Mathematics: For the development and optimization of algorithms, as well as for a deep understanding of the theoretical foundations of AI models.