It's interesting how (according to these charts) Bengaluru alone has more software engineering openings than the entire USA, and NYC has much more tech jobs than SF, on par with Pune.
This, and the absence of .NET technologies from the list (as noted elsewhere in the thread) makes me take this whole article with a large grain of salt.
India has a huge fake jobs problem. I think it is because of the number of "HR consultants" who constantly need to refresh their databases with "fresh" resumes. I've seen the same jobs being posted for over 8 years with no change whatsoever other than the keyword updates.
That's a funny mechanism. So these are fake jobs that HR consultants (recruiters?) use to harvest resumes?
What's the angle here?
They can submit those resumes to other positions.
This type of recruiter often is paid based on # of resumes furnished, not actually filling the position, so the incentives are completely misaligned.
Quickly checking db, SF bay area has quite a bit more than NYC. There are clearly a lot of .NET jobs too but didnt make it to cutoff. I will see if I can include metro areas when I get a chance.
I’m not sure how the list is being compiled but LinkedIn tells me there’s 10k jobs for “software engineer” in a 25 miles radius from me in the Bay Area. Either this data set is incomplete or LinkedIn is lying. Most likely it is both.
I got ~5K if I include Bay Area, tho my data only covers jobs that are active in the past 7d and am quite sure I have room to improve the crawl coverage. My hope is that this report is representative sample of trends.
So many LinkedIn jobs are fake.
> Bengaluru alone has more software engineering openings than the entire USA
That wouldn't exactly be surprising IMHO.
So there are no companies on Earth using (or at least hiring for) C# or .NET then... ?
There are definitely jobs for C# folks, where is mostly Finance. At least from what I’ve seen. Love .Net but they tend to gravitate towards Microsoft Corporate.
Most people, Java devs included, have incorporated another language into the quiver. Python perhaps. TypeScript for sure.
just didn't make the cutoff of top 10 categories I am tracking, I will update the report. iOS/android/c# are around same range of 2%
I would not be surprised if the answer is NO.
Certainly this AI report is prone to error and needs clarification. But it's a great starting point. Would love to see the page expanded on with sources. This:
business-software-applications: 20,248
software-engineering: 16,992
cybersecurity-engineering: 11,476
software-engineering-leadership: 10,608
data-and-analytics: 10,379
machine-learning-and-ai-engineering: 8,793
full-stack-software-engineering: 8,369
java-software-engineering: 8,114
software-quality-assurance-and-testing: 6,250
devops-engineering: 5,381
Should be broken down with a tree that shows location.
So is there a place where this compares to data from last year, or previous years?
Unfortunately I don't have it because I started working on this last year but I am curious to see how AI skills surface as the year progresses.
Good lord I though Indiana was leading the geographic listings for a moment.
Data is ex-china. Good luck to everyone looking for a new role in the new year.
What does “ex-china” mean, excluding China?
Edit: did a quick find-in-page on mobile for “china” and it appears 0 times. Though notably China is missing from the geographic charts
Yes, excluding china. I don’t have a lot of companies based in china in my crawl data currently.
That makes sense, they have their own ecosystem for posting jobs there.
Do they even hire engineers from abroad, or at least from the West?
Why not? Tiktok certainly needed engineers?
AI generated slop..
Crap like this should be banned.
Not all AI generated outputs are slop, usually it's the low effort prompts that create slop. When you bring in external data or extensive human curation it is almost certainly not slop. I think many people put all AI outputs in the slop bucket but this is unfair to those who put a lot of thinking in their AI interactions. Slop is not given by the LLM, but by the human effort associated to that task. For code, it is the quality of the testing framework that sets the bar.