I've recently been doing some (non-serious) job search. My background is STEM with a focus on computing.
What I have noticed is that the requirement to get a job with many tech companies seems to be much higher than the requirement to obtain a graduate degree and even after getting a PhD it does not seem that you would even match half of the requirements that these companies are demanding.
Does anyone else feel the same?
For example, I am currently looking at a company called Groq. For one of their few non-senior roles, it says: requires 2-10 years of experience in machine learning or software engineering, knowledge in hardware accelerators, familiarity with a subset of: linear algebra, Python, computer vision, natural language processing, C, reinforcement learning, FPGA, recommender system, C++, among others, and preferably publication in top-tier machine learning conferences.
I can firmly say that even PhDs whose primary research is in ML do not have these backgrounds that the jobs are looking for. This job description just doesn't seem to make sense in terms of what actually happens in school. A computer vision researcher is unlikely to be doing reinforcement learning and FPGA programming at the same time. A Python programmer is very unlikely to be somehow doing C programming at the same time and vice versa. Different people fundamentally uses different tools. Nobody designs integrated circuits while doing linear algebra (of any depth) at the same time.
This is just one job description out of hundreds I've seen and heard from other people. The numerous stories of STEM PhDs who are jobless or can't break out of academia seems to corroborate with my concern. I wonder if it is really true that it is harder to get a job nowadays than a graduate degree (or even a PhD) in STEM.
Can anyone who has been on both sides chime in on this?