AI is transforming the way businesses operate, and nearly every company is exploring how to leverage this technology.
As a result, the demand for AI and machine learning skills has skyrocketed in recent years.
With nearly four years of experience in AI/ML, I’ve decided to create the ultimate guide to help you enter this rapidly growing field.
Why work in AI/ML?
It’s no secret that AI and machine learning are some of the most desired technologies nowadays.
Being well-versed in these fields will open many career opportunities going forward, not to mention that you will be at the forefront of scientific advancement.
And to be blunt, you will be paid a lot.
According to Levelsfyi, the median salary for a machine learning engineer is £93k, and for an AI engineer is £75k. Whereas for a data scientist, it is £70k, and software engineer is £83k.
Don’t get me wrong; these are super high salaries on their own, but AI/ML will give you that edge, and the difference will likely grow more prominent in the future.
You also don’t need a PhD in computer science, maths, or physics to work on AI/ML. Good engineering and problem-solving skills, along with a good understanding of the fundamental ML concepts, are enough.
Most jobs are not research jobs but more implementing AI/ML solutions to real-life problems.
For example, I work as a machine learning engineer, but I don’t do research. I aim to use algorithms and apply them to business problems to benefit the customers and, thus, the company.
Below are jobs that use AI/ML:Machine Learning Engineer
AI Engineer
Research Scientist
Research Engineer
Data Scientist
Software Engineer (AI/ML focus)
Data Engineer (AI/ML focus)
Machine Learning Platform Engineer
Applied Scientist
They all have different requirements and skills, so there will be something that suits you well.
If you want to learn more about the roles above, I recommend reading some of my previous articles.
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