Job Market Health score
63/ 100
Strong
Stable · -1
- 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.
Medical equipment repairers
SOC 49-9062 · 49-0000 · Score reference month August 2026
Test, adjust, or repair biomedical or electromedical equipment.
In short
The national Job Market Health score is in the Strong band for August 2026.
$61,660Median annual wageOEWS May 2025
8,200Projected annual openingsBLS Employment Projections 2025-2035
+12.6%Projected growth2025–2035
65,990Total employmentOEWS May 2025
Latest interpretation
What stands out for medical equipment repairers
The clearest signals from the latest validated score, outlook and metro data.
Long-term outlook is the strongest component
Long-term outlook scores 89/100, compared with 46/100 for current demand, a 43-point difference.
JobMarketHealth score componentsLong-term growth is projected at 10% or more
BLS projects 8,200 average annual openings and +12.6% employment growth from 2025 to 2035. Projected openings are a modeled annual average, not vacancies open today.
BLS Employment ProjectionsLargest published metro market
New York-Newark-Jersey City, NY-NJ has the largest published metro employment count for medical equipment repairers, at 3,010 jobs. The next-largest published metro is Los Angeles-Long Beach-Anaheim, CA with 2,270 jobs. This measures employment scale, not market quality.
BLS OEWSLocal 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 medical equipment repairersSide-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 2663 / 100
View values: Job Market Health history
| Reference month | Score / 100 |
|---|---|
| Jan 25 | 61 |
| Feb 25 | 61 |
| Mar 25 | 61 |
| Apr 25 | 59 |
| May 25 | 60 |
| Jun 25 | 58 |
| Jul 25 | 57 |
| Aug 25 | 56 |
| Sep 25 | 57 |
| Oct 25 | 57 |
| Nov 25 | 57 |
| Dec 25 | 56 |
| Jan 26 | 56 |
| Feb 26 | 57 |
| Mar 26 | 60 |
| Apr 26 | 62 |
| May 26 | 64 |
| Jun 26 | 65 |
| Jul 26 | 64 |
| Aug 26 | 63 |
Score components
The three published inputs behind the composite · each 0–100
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.
| Metro area | Employment | Jobs per 1,000 | Median annual wage |
|---|---|---|---|
| New York-Newark-Jersey City, NY-NJ | 3,010 | 0.32 | $68,460 |
| Los Angeles-Long Beach-Anaheim, CA | 2,270 | 0.36 | $62,160 |
| Phoenix-Mesa-Chandler, AZ | 2,140 | 0.90 | $63,060 |
| Chicago-Naperville-Elgin, IL-IN | 1,940 | 0.43 | $68,580 |
| Dallas-Fort Worth-Arlington, TX | 1,670 | 0.41 | $58,680 |
| Boston-Cambridge-Newton, MA-NH | 1,660 | 0.61 | $78,480 |
| Minneapolis-St. Paul-Bloomington, MN-WI | 1,440 | 0.74 | $63,740 |
| Miami-Fort Lauderdale-West Palm Beach, FL | 1,140 | 0.41 | $56,150 |
| Atlanta-Sandy Springs-Roswell, GA | 1,130 | 0.39 | $49,710 |
| Houston-Pasadena-The Woodlands, TX | 1,090 | 0.33 | $61,080 |
Education & training
Typical entry requirements · BLS Employment Projections 2025-2035
Top skills
Occupation profile · O*NET 31.0 Database
- Repairing
- Equipment Maintenance
- Troubleshooting
- Operations Monitoring
- Quality Control Analysis
- Critical Thinking
- Reading Comprehension
- Active Learning
- Active Listening
- Complex Problem Solving
Also known as: Biomedical Electronics Technician (Biomed Electronics Tech), Biomedical Engineering Technician (Biomed Engineering Tech), Biomedical Equipment Technician (BMET), Biomedical Technician (Biomed Tech), Dental Equipment Technician (Dental Equipment Tech), Durable Medical Equipment Technician (DME Tech)
AI & this occupation
How AI relates to Medical equipment repairers work
Across 4 research exposure measures, Medical equipment repairers is in the middle 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.
The saved Anthropic task-exposure benchmark records a zero index for this occupation. This is not proof of no AI use; the observation window is not recorded in this saved release.
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.
Exposure measures (kept separate)
- GPTs are GPTs exposure (β, GPT-4 rated): 0.30 of 1, national percentile 48 (middle third)
- Microsoft AI applicability: 0.16 of 1, national percentile 54 (middle third)
- AIOE (Felten, Raj & Seamans): -0.28 (standardized), national percentile 44 (middle third)
- OECD AI Capability Gap (lower gap = higher potential exposure): gap 3.4 of 23, national percentile 47 (middle 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 0.00 (demand 3.00 of 5)
- Social interaction: gap 0.50 (demand 2.50 of 5)
- Problem solving: gap 0.80 (demand 2.80 of 5)
- Creativity: gap 0.00 (demand 1.55 of 5)
- Metacognition & critical thinking: gap 1.05 (demand 3.05 of 5)
- Knowledge, learning & memory: gap 0.50 (demand 3.50 of 5)
- Vision: gap 0.35 (demand 3.35 of 5)
- Manipulation: gap 1.85 (demand 3.85 of 5)
- Robotic intelligence: gap 1.05 (demand 3.05 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 Medical equipment repairers 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
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.
Related occupations
O*NET® lists these occupations as related. Each link opens the same published view of score, wages and outlook.
Evidence record
JobMarketHealth derived indicator; not a government statistic. The composite score is national and occupation level.
- Occupation
- Medical equipment repairers
- SOC code
- 49-9062
- Geography
- United States
- Reference month
- August 2026
- Published Job Market Health score
- 63 / 100
- Restated score
- 63 / 100
- Band
- Strong
- Current Demand component
- 46 / 10050% weight
- Occupation Fundamentals component
- 74 / 10030% weight
- Long-Term Outlook component
- 89 / 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
- 2026-10-02T15:32:42.508Z
- First published at
- Sep 29, 2026
- Recalculated at
- Oct 2, 2026
- Canonical record URL
- https://jobmarkethealth.com/occupations/medical-equipment-repairers#evidence-record
- Derived by
- JobMarketHealth
MethodologyBLS JOLTSBLS CESBLS Employment ProjectionsHow to citeNational Job Market Health release, August 2026
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.