Generative AI
An article on the most common LLM development challenges I’ve encountered, effective mitigation strategies, and a career-defining interview mistake
I’ve always been the type to dive deep into a subject and specialize to obsession. When I graduated from my master’s in data science, the obsession I had was with computer vision; specifically, computer vision to apply towards neuroscience or mental health applications. I was set on becoming a “computer vision engineer” (but “machine learning engineer” would be okay too) in the mental health field, despite my mentors urging me to broaden my scope and get my foot in the door. I silenced my own wary voices, convinced that the right team would recognize my “expertise”.
Luckily, my theory seemed to work; I landed interviews with several mental health companies. But then came one of my biggest interview mistakes. In the final round for my top choice — a company I loved — I made an error that still makes me internally cringe when I reflect. The role was NLP-focused, working with text data, but I couldn’t help expressing my interest in…