I recently came across a Reddit post that resonated with me, and I think it’s worth exploring further. The author, a linguistics graduate, is struggling to find a job in traditional NLP (natural language processing) despite having experience in intent classification models, sentiment analysis, and machine translation. They’re not alone in their frustration. With the rise of genAI (generalized artificial intelligence), it seems like traditional NLP jobs are drying up.
The author’s story is relatable. They fell in love with machine learning and wanted to apply their linguistics skills to create AI-driven data insights. However, after four years of working in the industry, they’re feeling defeated and hopeless. The job market seems to be saturated with senior applicants, and the only jobs available are ‘AI Engineer’ positions that they’re not interested in.
The author’s question is valid: is there still demand for non-genAI NLP jobs? Should they hold onto their dream until the job market improves or genAI hype dies down? Or is traditional NLP dead, and they should consider a career change?
I think it’s essential to acknowledge that the job market is constantly evolving. While genAI might be the current trend, it’s unlikely to replace traditional NLP entirely. There will always be a need for professionals who can work with data, preprocess datasets, and apply ML techniques.
Perhaps the solution lies in upskilling and reskilling. The author has already tried MLOps courses, but they might need to explore other areas like predictive modeling or data science. It’s also crucial to network and attend industry events to stay updated on the latest developments and job opportunities.
Lastly, I want to emphasize that it’s okay to feel burnt out and defeated. It’s essential to take a step back, reassess your goals, and prioritize your well-being. If you’re struggling to find a job in traditional NLP, consider taking a break, freelancing, or exploring related fields like data analysis or science writing.
The job market might be challenging, but it’s not impossible. With persistence, hard work, and a willingness to adapt, you can still find a fulfilling career in traditional NLP.