Machine learning is a highly competitive field, attracting top tech talent and experienced researchers, with tight deadlines and high expectations, making entry-level roles scarce.
#1 Intense Competition
High-pressure, experimental projects with tight deadlines, high expectations, and responsibilities can be stimulating for those who thrive under pressure but may not be suitable for everyone.
#2 High pressure
Office politics involve intense workplace dynamics, including board clashes, employee firings, and unpredictable work environments. While excitement may be worth it, some may consider reconsidering it.
#3 Office Politics
#4 Investment in Education
Investing time and money in education for AI or machine learning requires a strong foundation in math and computer science, requiring years of study and self-study plans.
#5The Time
AI development takes time and effort, potentially requiring months or years of experience. Career changes may require significant sacrifices and may not be feasible for some.
#6 Rapidly Evolving Technology
Machine learning constantly evolves, necessitating constant learning and adaptation. This can be overwhelming for those not accustomed to fast-paced changes.
#7 Less Competitive Options
Tech career paths include data science, data engineering, data analyst, and business analyst roles, which require less specialized skills and are open to junior candidates.