The top ten highest-paid tech skills can make you a lot of money – here’s how much

The skyrocketing interest in generative AI and recent layoffs have caused workers to experience a lot of job insecurity in the tech job market. However, a new report shows that picking up one of these ten tech skills could increase your marketability to employers, and even your salary. 

On Wednesday, Indeed shared a list of the top ten highest-paid skills in tech, as well as a quick glimpse at the tech job market, which isn’t as bleak as you might think.

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This past January, 30,995 tech employees were laid off, and even though that sounds like a high number, it was “barely” one-third of the employees laid off last January, according to the report. 

The good news for job seekers is the number one skill on Indeed’s highest-paid tech skills list — generative AI — can be learned through deep dives into free but high-quality online courses from Amazon, IBM, and other reputable companies, which ZDNET has covered at length.

In fact, the majority of the highest-paid skills in tech are related to AI in some capacity, with generative AI, System-on-chip (SoC), and deep learning in the first three spots.

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The average salary potential for workers with generative AI and SoC skills is around $174,000, with a 47% difference in salary potential with the skill versus those without. Employees with skills in deep learning trail slightly behind with an average salary potential of $170,939, and a 44% difference with the skill. 

The rest of the skills all range between the $165,000 to $169,000 salary potential and include Torch, PyTorch, Computer vision, SystemVerilog, Mesos, Rust, and Elixir. You can find each skill’s description, average salary potential, and percent difference in the chart below. 

After seeing the skills list and their lucrative potential salaries, you might be curious about what roles necessitate these skills to see if any interest you. 

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Indeed identified the top five roles requiring these skills as data scientist, machine learning engineer, software engineer, research scientist, full stack developer, deep learning engineer, and software architect.