— Occupational IQ research

Average IQ of Machine Learning Engineers: 130

Average IQ

130

Percentile

98th

Why Machine Learning Engineers cluster at this IQ level

The profession selects for, and then trains, the cognitive abilities required to do the work. Machine Learning Engineers show particular strength in numeric, logical, abstract — the cognitive axes that most predict performance in this field. These traits cluster because the work itself demands them and because entry filters (degrees, exams, certifications, interviews) screen for them.

Within the tech field, Machine Learning Engineers sit relatively high compared to peers. The standard deviation within the occupation is typically 10-15 IQ points, meaning roughly two-thirds of working Machine Learning Engineers fall in the IQ 115-145 band.

Cognitive demands of the work

The IQ figure for Machine Learning Engineers reflects the cognitive load of the actual job:

Sustained reasoning under uncertainty. The work requires holding multiple constraints in working memory while reasoning through partial information.
Pattern recognition. Recognizing structurally-similar problems despite surface differences is a major performance driver.
Communication precision. Whether technical or interpersonal, the work demands articulating ideas without ambiguity.
Decision-making with consequences. Errors carry weight — financial, physical, reputational, or all three.

Profession	Avg IQ	Percentile
Software Engineer	130	98th
Computer Scientist	130	98th
Data Scientist	129	97th
Programmer	124	95th
Game Developer	121	92th
Machine Learning Engineers	130	98th

Find out YOUR exact IQ

Take a 20-minute calibrated test and see how you compare across all six cognitive axes — including the ones Machine Learning Engineers score highest on.

What this average does NOT mean

An occupational IQ average is a statistical mean, not a hiring criterion. 130-level cognition is the typical Machine Learning Engineer, not the minimum. Plenty of working Machine Learning Engineers score below 115, succeeding through experience, conscientiousness, deep domain knowledge, and motivation — none of which IQ tests measure.

The average also describes the people who entered and stayed in the profession. It does not predict whether you specifically could succeed as a machine learning engineer. Personal interest, work ethic, and circumstance matter at least as much.

How to read your own IQ against the Machine Learning Engineer average

If you score within 120-140: you are in the typical range for Machine Learning Engineers. Your cognitive profile is well-matched to the work.
If you score above 145: you have meaningful cognitive headroom. The abstract demands of the role are likely to feel easier than for most peers.
If you score below 120: the profession is still entirely accessible to you. Many successful Machine Learning Engineers score below the mean, relying more on structured systems, persistence, and specialization than raw speed.

Frequently asked

What is the average IQ of a machine learning engineer?

The estimated average IQ for Machine Learning Engineers is 130, based on occupational sampling and GRE-derived data. This corresponds to roughly the 98th percentile.

Do you need a high IQ to be a machine learning engineer?

There is no formal IQ requirement. The 130 average reflects who tends to enter and stay in the profession, not a minimum threshold. Successful Machine Learning Engineers exist well above and below this number.

What's the highest-IQ profession?

Physicists, mathematicians, and astronomers cluster around 131-132 average IQ. The top tier of professions are within 3-4 IQ points of each other.