I would like to know the demand for AI Engineers in US and their possible career growth.
If you would like to know the answer in a single string, most likely this will be the answer: New York City claims to be the capital booming industry in artificial intelligence.
AI is now being used in an ever-expanding array of products and AI adoption was also accelerated at an unprecedented rate among almost all sectors. The expanding applications for AI has resulted in escalated demand for skilled AI talent.
The US-based organizations are ready to spend more than 1 billion dollars by the year 2020 for grabbing AI talent from wherever it can find in the market.
Among the top AI and Machine Learning jobs – AI engineer is one of the highly paid and demanded professions. According to Indeed.com, the average salary of an "artificial intelligence engineer" – in San Francisco is about $169,930 per year.
AI engineers are highly sought by financial services, and government agencies. This includes top firms like Booz Allen Hamilton, EY, and McKinsey & Company. Multinationals like Apple Inc., Amazon.com Inc., Alphabet Inc., Facebook Inc. and Uber Technologies Inc. have been paying huge salaries to their highly technical candidates with machine learning skills.
Interestingly, New York and not San Francisco is the leading city that boasts the highest percentage of job postings with AI and machine learning descriptions, with more than 11% of national job postings.
As per the report by Indeed – the leading global job search portal, the job postings for AI and machine learning skills have doubled since 2015. As a result, the competition to recruit AI talent is on high. With such severe talent crunch in the market, the young aspirants who wish to make their career in AI, can strike a gold in the market by acquiring the right skills and qualifications.
In a nutshell, head to the US, if you wish to make your career in AI, as most of the job openings and demand is concentrated there – more specifically – NYC – the New York City!
Perhaps we could create a model containing a few object types.
- Cities of the world
- AI departments, groups, and lone positions
- Employing entities (companies, university departments and schools, government agencies)
- The brains of humans in people studying science and technology
- Incentives for hiring managers and those hired (financial, perks, prestige, health, pension)
In such a simulation, what would result? How would an engineer position themselves to have a optimally enjoyable and profitable career?
Of course, with AI, the model needs another twist. Consider this seventh object type.
- Auto-generated system
In this game, it may be important for the engineer to position themselves to reduce the likelihood that a peer will produce a system that replaces her or him. This is interesting to me because I've, since the last century, always tried to find patterns in my work and automate them recursively. In some cases, I quit jobs because I succeeded and some automation was handling what they hired me to do. I'm fine with that because the incentives above are not my primary motivation and I'm not particularly attached to humanism. That is a question each engineer must ask themselves when navigating this particular decision tree.
With AI being a primary objective of technologists since before the first mechanical calculating device, long before the invention of the digital circuit, and with the profitability of everything from automated vehicles to high speed trading agents to artificial buddies to business intelligence systems, it is highly unlikely that the value of an AI engineer will decline until this seven object type enters our simulation. At that point most all careers will have been replaced by AI engineering achievements.
It's like the sustainability of solar energy. Theoretically, solar energy acquisition for industry and homes is not perfectly sustainable. The sun could go supernova or die out. Practically, solar energy is sustainable because under those two conditions, industry and homes will be either converted to plasma or frozen in orbit.
AI engineering as a career in one of the high technology cities in the U.S. or any other relatively well developed city in any stable nation is a fairly rational bet. If in robotics, pick a city that has the appropriate laboratory space and on location teams. For data center work, a contractor can work from the middle of a desert if there's an Internet connection and a supply line of food and water.