The AI engineer skills gap

In this episode of the Practical AI podcast, Daniel Whitenack and Chris Benson are joined by Ramin Mohammadi to discuss the evolving roles of AI, machine learning, and data science professionals in both industry and academia. The conversation explores how the job market has shifted from valuing theoretical knowledge to prioritizing practical skills in building and deploying AI systems. They address the challenges faced by new graduates, the widening gap between academic curricula and industry needs, and the impact of generative AI on entry-level positions. The discussion also covers how academia and industry can collaborate to bridge the skills gap and prepare students for the future of AI, including the importance of hands-on experience, portfolio development, and continuous learning.