Engineering teachers, postsecondary

SOC 25-1032 · 25-0000 · Score reference month August 2026

Teach courses pertaining to the application of physical laws and principles of engineering for the development of machines, materials, instruments, processes, and services. Includes teachers of subjects such as chemical, civil, electrical, industrial, mechanical, mineral, and petroleum engineering. Includes both teachers primarily engaged in teaching and those who do a combination of teaching and research.

In short

The national Job Market Health score is in the Balanced band for August 2026.

Job Market Health score

52/ 100
Balanced

Stable · -1

Confidence
High
Restated score
52
Methodology
v1.0
Geography
US
  • At least 90% of required inputs and occupation-industry mapping are covered.

Job Market Health scores are derived indicators based on published data, informational only, not a forecast or guarantee.

$109,270Median annual wageOEWS May 2025
3,900Projected annual openingsBLS Employment Projections 2025-2035
+7.8%Projected growth2025–2035
40,270Total employmentOEWS May 2025

Latest interpretation

What stands out for engineering teachers, postsecondary

The clearest signals from the latest validated score, outlook and metro data.

Long-term outlook is the strongest component

Long-term outlook scores 69/100, compared with 46/100 for current demand, a 23-point difference.

JobMarketHealth score components

Published long-term outlook

BLS projects 3,900 average annual openings and +7.8% employment growth from 2025 to 2035. Projected openings are a modeled annual average, not vacancies open today.

BLS Employment Projections

Largest published metro market

New York-Newark-Jersey City, NY-NJ has the largest published metro employment count for engineering teachers, postsecondary, at 2,600 jobs. The next-largest published metro is Boston-Cambridge-Newton, MA-NH with 2,010 jobs. This measures employment scale, not market quality.

BLS OEWS

Local market context

QCEW industry conditions for this occupation’s employment mix

Choose a state to see how the industries that employ this occupation are performing locally.

Choose a state above to explore its available industry context.

How to read this section

QCEW measures employment and wages by industry, not by occupation. We weight those industry conditions using the published industry mix for this occupation. These figures describe the industries that employ this occupation; they are not direct counts of people working in the occupation or jobs currently open.

Source: BLS QCEW. This section is not part of the national 0 to 100 Job Market Health score. See the methodology.

Compare states for engineering teachers, postsecondarySide-by-side published industry conditions for two or three states. There is no state-level health score; the 0 to 100 score is national.

How to read this page

The score is a national composite from 0 to 100 that weights near term hiring demand at 50 percent, the occupation's own employment fundamentals at 30 percent, and long-term outlook at 20 percent. Wages and occupation profile details are context shown alongside it, not score inputs. See the full methodology.

Median annual wage and metro employment come from BLS OEWS, which is annual. Projected annual openings and projected growth come from BLS Employment Projections and describe the published projection horizon, so they are not a count of jobs open today. Values shown as not published are suppressed by the source rather than filled in here.

Job Market Health trend

Published composite score · 0–100 · by reference month

Latest published values
  • Aug 2652 / 100
View values: Job Market Health history
Job Market Health history
Reference monthScore / 100
Jan 2565
Feb 2565
Mar 2565
Apr 2564
May 2565
Jun 2564
Jul 2562
Aug 2560
Sep 2560
Oct 2556
Nov 2555
Dec 2553
Jan 2657
Feb 2653
Mar 2654
Apr 2652
May 2654
Jun 2653
Jul 2653
Aug 2652

Score components

The three published inputs behind the composite · each 0–100

Current demand46 / 100
Occupation fundamentals52 / 100
Long-term outlook69 / 100

Largest metro markets by employment

OEWS employment count, where the jobs are, not a quality ranking

OEWS May 2025. These occupation counts describe the survey reference period.

Linked metro names open overall job-market profiles.

Compare cities for this career →

Employment · number of jobs

  • New York-Newark-Jersey City, NY-NJ2,600
  • Boston-Cambridge-Newton, MA-NH2,010
  • Philadelphia-Camden-Wilmington, PA-NJ-DE-MD1,700
  • College Station-Bryan, TX1,160
  • Los Angeles-Long Beach-Anaheim, CA1,130
  • Pittsburgh, PA760
  • Ann Arbor, MI710
  • Austin-Round Rock-San Marcos, TX630
  • Dallas-Fort Worth-Arlington, TX600
  • Washington-Arlington-Alexandria, DC-VA-MD-WV590
Largest metro markets by employment
Metro areaEmploymentJobs per 1,000Median annual wage
New York-Newark-Jersey City, NY-NJ2,6000.27$123,210
Boston-Cambridge-Newton, MA-NH2,0100.74$135,480
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD1,7000.59$79,210
College Station-Bryan, TX1,1608.67$129,110
Los Angeles-Long Beach-Anaheim, CA1,1300.18$137,760
Pittsburgh, PA7600.68$77,870
Ann Arbor, MI7103.22$140,450
Austin-Round Rock-San Marcos, TX6300.49$132,130
Dallas-Fort Worth-Arlington, TX6000.15$125,140
Washington-Arlington-Alexandria, DC-VA-MD-WV5900.19$126,210

Education & training

Typical entry requirements · BLS Employment Projections 2025-2035

Typical education
Doctoral or professional degree
Work experience
None
On-the-job training
None
Projected employment
54,900 jobs

Top skills

Occupation profile · O*NET 31.0 Database

  • Instructing
  • Learning Strategies
  • Speaking
  • Active Listening
  • Reading Comprehension
  • Critical Thinking
  • Mathematics
  • Writing
  • Judgment and Decision Making
  • Active Learning

Also known as: Assistant Professor, Associate Professor, Chemical Engineering Professor, Electrical Engineering Professor, Engineering Instructor, Engineering Professor

AI & this occupation

How AI relates to Engineering teachers, postsecondary work

Across 4 research exposure measures, Engineering teachers, postsecondary is in the higher technical AI exposure band based on the mean of the available source-specific percentile ranks. Exposure describes how much of the work the studied AI capabilities could technically assist with; it is not a forecast of job loss.

Observed use of Claude for this occupation's tasks is in the higher third of occupations in the Anthropic Economic Index, a dated observed task-exposure benchmark, not conversation share or the share of workers using AI. Its observation window is not recorded in this saved release.

In the task mix derived from the March 27, 2025 Anthropic release, 70.1% followed augmentation patterns (people iterating, validating or learning with AI), based on 14 matched tasks.

JobMarketHealth has not measured an AI effect on this occupation's employment or wages, and these figures do not enter its scores; there is no clear evidence of displacement in the data shown here.

Technical AI exposureHigher exposureMean of 4 available source-specific percentile ranks (4 measures checked); fixed exposure bands, not a national rank of the composite
Dated Claude task exposureHigher thirdObserved task-exposure benchmark 0.359; observation window not recorded
Business AI use (BTOS Core)24.6%U.S. businesses using AI, two weeks ending 2026-10-04; all industries, not this occupation
Historical task mix (2025)70.1% augmentationMarch 27, 2025 release; 29.9% automation, 14 matched tasks
Measured labor-market effectNot estimatedJobMarketHealth does not attribute employment or wage changes to AI

Exposure measures (kept separate)

  • GPTs are GPTs exposure (β, GPT-4 rated): 0.50 of 1, national percentile 78 (higher third)
  • Microsoft AI applicability: 0.33 of 1, national percentile 95 (higher third)
  • AIOE (Felten, Raj & Seamans): 1.35 (standardized), national percentile 93 (higher third)
  • OECD AI Capability Gap (lower gap = higher potential exposure): gap 6.4 of 23, national percentile 13 (lower third)
OECD capability gap by domain

As published by the OECD: the gap between what the occupation demands (0-5) and current AI capability in each domain. A lower gap means AI is closer to the requirement (higher potential exposure); 0 means AI already meets it or the domain is not relevant.

  • Language: gap 1.15 (demand 4.15 of 5)
  • Social interaction: gap 2.00 (demand 4.00 of 5)
  • Problem solving: gap 2.15 (demand 4.15 of 5)
  • Creativity: gap 0.35 (demand 3.35 of 5)
  • Metacognition & critical thinking: gap 2.25 (demand 4.25 of 5)
  • Knowledge, learning & memory: gap 1.75 (demand 4.75 of 5)
  • Vision: gap 0.00 (demand 0.80 of 5)
  • Manipulation: gap 0.00 (demand 0.05 of 5)
  • Robotic intelligence: gap 0.00 (demand 0.00 of 5)

National context: what businesses used generative AI for

From the Census 2025-26 BTOS AI Supplement (all industries; businesses whose employees used generative AI). Census did not measure Engineering teachers, postsecondary specifically.

  • Writing or editing documents, emails, or communications: 85.4%
  • Searching for information or technical help: 49.9%
  • Interpreting, analyzing, translating, or summarizing documents: 44.6%
  • Information processing, paperwork, or filing: 34.7%

Exposure and observed usage are separate measures and neither equals job loss. Census BTOS figures are business-level surveys and are not occupation-specific. Sources: GPTs are GPTs occupation exposure; Microsoft Working with AI: AI applicability; AI Occupational Exposure (AIOE); OECD AI Exposure Measure (AI Capability Gap); Anthropic Economic Index; Census BTOS Core AI Use; Census BTOS AI Supplement 2025-26. These figures do not affect Job Market Health scores. Explore AI & Jobs · How we use AI data.

Sources and methodology

The datasets behind the figures on this page

Job Market Health score
Score for reference month August 2026 · methodology v1.0 · MethodologyScore last recalculated Oct 2, 2026 · First published Sep 29, 2026
BLS Occupational Employment and Wage Statistics
Employment, wages and largest metros · OEWS May 2025 · publisher release May 15, 2026 · About this sourceRetrieved Sep 17, 2026
BLS Employment Projections
Projected growth, openings, education and training · BLS Employment Projections 2025-2035 · publisher release Aug 27, 2026 · About this sourceRetrieved Sep 17, 2026
O*NET
Skills, alternate titles and related occupations · O*NET 31.0 Database · publisher release date not verified · About this sourceRetrieved Oct 19, 2026

Values marked “Not published” are suppressed or not published by the source. We leave them blank rather than estimating them. Pipeline status for every source is on Data Status.

Evidence record

JobMarketHealth derived indicator; not a government statistic. The composite score is national and occupation level.

Occupation
Engineering teachers, postsecondary
SOC code
25-1032
Geography
United States
Reference month
August 2026
Published Job Market Health score
52 / 100
Restated score
52 / 100
Band
Balanced
Current Demand component
46 / 10050% weight
Occupation Fundamentals component
52 / 10030% weight
Long-Term Outlook component
69 / 10020% weight
Confidence
HighAt least 90% of required inputs and occupation-industry mapping are covered.
Methodology version
v1.0
Source vintage: Annual
EP-2025-2035|CPS-25b-2025|OEWS-2020-2025
Source vintage: Monthly calculated at
2026-10-02T15:32:24.434Z
First published at
Sep 29, 2026
Recalculated at
Oct 2, 2026
Canonical record URL
https://jobmarkethealth.com/occupations/engineering-teachers-postsecondary#evidence-record
Derived by
JobMarketHealth

Keep going

Learn how to judge a market from these numbers in how to tell if a job market is healthy, or why projected growth and annual openings often disagree in projected growth vs projected annual openings. Coverage, revisions and limits are explained on about the data.

The datasets behind these figures, and what each one can and cannot show, are set out on data sources.