Main image of article Which Company Pays Its Staff Engineers the Most?

OpenAI, the A.I. company behind the famous ChatGPT chatbot, is drawing a lot of buzz right now. Anyone interested in the A.I. and machine-learning space is probably wondering whether the company has any openings—and how much it pays.

According to’s 2023 Mid-Year Compensation Report, which relies on crowdsourced information, OpenAI pays experienced staff engineers more than other companies in tech, including ones with pretty deep pockets. Here’s the breakdown:

OpenAI’s high salaries shouldn’t come as a surprise, considering a.) the company has attracted an insane level of investment, b.) highly specialized and experienced engineers demand high compensation, and c.) this level of compensation is designed to fend off aggressive competitors for talent. Tech giants have shown a willingness to pay absurd amounts of money for those skilled in A.I., machine learning, and automation.

Analyzing by median total compensation doesn’t paint the whole picture, of course; at richly financed companies like Netflix, Google, and Microsoft, star engineers and researchers (and managers) can comfortably earn millions of dollars, especially if part of their compensation is tethered to stock price. Nonetheless,’s data suggests that mastering the complicated nuances of artificial intelligence can pay off in a big way.’s report also states that A.I. and machine learning have enjoyed a 2.7 percent uptick in median compensation between the second half of 2022 and the first half of this year, just behind DevOps, distributed systems, and VR/AR (virtual reality/augmented reality). Even if you don’t land a job at OpenAI or some other prominent A.I. company, organizations everywhere are increasingly interested in bringing aboard tech professionals with at least a familiarity with the principles of A.I. and machine learning.

Nearly half (49 percent) of business leaders recently surveyed by Upwork said they want to hire more full-time staff and freelancers as a result of generative A.I. initiatives. While A.I. and machine learning are complicated and often difficult topics to learn, doing so can open up a plethora of opportunities in the space, especially as organizations free up more budget to make their apps and services “smarter.”