How I Cracked an AI Engineer Role
Published:Dec 27, 2025 11:04
•1 min read
•r/learnmachinelearning
Analysis
This article, sourced from Reddit's r/learnmachinelearning, offers practical advice for aspiring AI engineers based on the author's personal experience. It highlights the importance of strong Python skills, familiarity with core libraries like NumPy, Pandas, Scikit-learn, PyTorch, and TensorFlow, and a solid understanding of mathematical concepts. The author emphasizes the need to go beyond theoretical knowledge and practice implementing machine learning algorithms from scratch. The advice is tailored to the competitive job market of 2025/2026, making it relevant for current job seekers. The article's strength lies in its actionable tips and real-world perspective, providing valuable guidance for those navigating the AI job market.
Key Takeaways
- •Master Python and core AI/ML libraries.
- •Practice implementing algorithms from scratch.
- •Strengthen your understanding of linear algebra and calculus.
Reference
“Python is a must. Around 70–80% of AI ML job postings expect solid Python skills, so there is no way around it.”