Regardless of how much experience you have in the fields of AI or Machine Learning, I am sure you are well aware that Silicon Valley is the biggest hub for tech companies in the world.

The Bay Area is hands down the place with the greatest concentration of startups, venture capital, and digital talent on the planet. However, that doesn’t mean it is the place with the best opportunities to land your dream job.

In fact, Silicon Valley might be too competitive for Junior Engineers, who might be better off starting their careers in less popular places.

Job opportunities are purely determined by the law of offer and demand, so ideally, you don’t just want to be where the most vacancies are found. You want to be in the place with the most open vacancies per skilled applicant.

It’s as simple as that, and therefore I have prepared a list after researching job openings and available talent on the biggest job site on the internet, that is, Linkedin.

How to Do Your Research

When researching the job market on Linkedin, it is important to be very careful with the words you use.

For example, you might be tempted to search for “machine learning engineer” or “data scientist” jobs in different cities and see how many vacancies are available.

The problem with this is the search engine will return jobs containing any of these words. So the result is a mix containing not only our desired vacancies in AI or ML but also jobs in teaching (learning), sales (machine), or any kind of scientist/engineer.

So I recommend you narrow your search by specific technical skills.

First, you search for jobs containing your desired skill in a particular city.

Then, search for people naming that skill in their profile in that place.

And voilá, now you have a good picture of the rate jobs available/skilled talent in that city.

For example, in this case, I made my research using two searches:

• Python: Python is by far the most used language in AI so it will give us a good general picture of the AI market in a particular place.
• Tensorflow: as you all know, not all Python jobs are in ML/AI, many are positions for pure backend developers, so you should also research a technical skill used only in AI. For this purpose, I think Tensorflow is the most popular framework we can research.

Of course, feel free to use any other languages of your choice, the trends should look similar anyway.

The point here is to use a popular language as starting point to select interesting cities and then look at them deeper using a more specific skill.

It happens very often that some towns are very popular for startups (therefore have a more software-development-oriented market), others are dominated by industry, and others are more research-oriented.

If a realtively small town has an important AI Research Centre, it will reflect in the job market. That’s why it is important to be specific in your search.

OK, now that I explained how I did my research so let’s jump into the results.

These are the Top 10 Cities With Most Vacancies in AI/ML per Candidate

Alright, so this is the list for the top 10 cities for AI jobs, ranked both by Python and Tensorflow jobs per candidate:

Ranking for Python Jobs / Potential Candidate on Linkedin:

• Nashville: 0.168
• Charlotte: 0.162
• Austin: 0.144
• Dallas: 0.143
• Columbus: 0.139
• Denver: 0.122
• Atlanta: 0.116
• Raleigh:0.112
• Chicago: 0.106
• Philadelphia: 0.103

Let’s plot these results to have a better picture:

Ranking for Tensforflow jobs / Potential Candidate on Linkedin:

• Charlotte: 0.259
• Nashville: 0.256
• Columbus: 0.170
• Austin: 0.134
• Chicago: 0.133
• Philadelphia: 0.133
• Atlanta: 0.132
• Dallas: 0.126
• Denver: 0.124
• Raleigh: 0.124

Here is a quick plot:

You can download the source CSV here.

Conclusion

Well, after looking at the data generously provided by Linkedin, I think there is a pretty obvious conclusion: city popularity is a bad thing for candidates looking for jobs.

As it happens with the rental market, when cities become too popular for tech jobs people start flocking there as well, and therefore competition increases.

For example, Charlotte has 2.6 more Tensorflow jobs available per candidate than the Bay Area, that might come as a surprise and should be taken into account.

So, all in all, my key takeaway is medium-sized cities that are not overly popular are the best destinations as a job applicant. You are a scarce resource in this ecosystem, therefore your value will increase, and landing an interesting job in AI/ML will be easier there.