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Medical Equipment Repairers

Occupation · SOC 49-9062.00

Test, adjust, or repair biomedical or electromedical equipment.

Also called: Biomedical Electronics Technician (Biomed Electronics Tech) · Biomedical Equipment Technician (BMET) · Biomedical Technician (Biomed Tech) · Service Technician (Service Tech) · Biomedical Engineering Technician (Biomed Engineering Tech) · Dental Equipment Technician (Dental Equipment Tech) · Durable Medical Equipment Technician (DME Tech) · Medical Equipment Service Tech (Medical Equipment Service Technician) · Repair Technician (Repair Tech) · X-ray Service Engineer · Biomedical Equipment Specialist (Biomed Equipment Specialist) · Biomedical Equipment Support Specialist (Biomed Equipment Support Specialist)

Job family: Installation, Maintenance, and Repair Occupations

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Download .md

A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /roles/role-49-9062-00/context.md directly.

AI work map

A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.

44th-percentile task overlap — yet about 7,300 openings a year (+12.9% projected, BLS) . What exposure means →

AI & job outlook

What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.

Exposure to current AI

Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.

Measure Rank vs all occupations Percentile Score
Overall AI exposure (Felten et al.) Moderate 41st -0.3
LLM task exposure, γ (OpenAI / Eloundou) Moderate 41st 0.5
AI assistant applicability (Microsoft) Moderate 52nd 0.2

OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.2), with simple added tooling (β 0.3), and including AI-powered software (γ 0.5). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.

This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.

Historical automation estimate (2013)

A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.

Frey–Osborne probability 0.3 · 38th percentile among occupations · Moderate

How AI is actually used in this job

Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.

Test or calibrate components or equipment, following manufacturers' manuals and troubleshooting techniques, using hand tools, power tools, or measuring devices. 1.1%
Explain or demonstrate correct operation or preventive maintenance of medical equipment to personnel. 0.2%

Job outlook

Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.

Outlook Growing fast · +12.9% by 2034
Projected annual openings 7,300
Employment 2024 → 2034 68,000 → 76,800

“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.

Where this work sits on the global GenAI gradient

The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.

21% mean task exposure (2025)
37th percentile of 427 placed occupations
+3 pts shift 2023 → 2025
International occupation (ISCO-08) Task exposure (2025) Most tasks fall in
Precision-instrument Makers and Repairers · 7311 21% Not exposed

Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.

Tasks

All 19 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.

Work activities

Knowledge, skills & abilities

O*NET importance rating, from 1 (not important) to 5 (extremely important).

Transferable skills

Repairing 4.3
Equipment Maintenance 4.0
Troubleshooting 3.9
Operations Monitoring 3.5
Quality Control Analysis 3.4
Complex Problem Solving 3.0
Equipment Selection 3.0
Judgment and Decision Making 3.0
Systems Analysis 3.0
Time Management 3.0

Knowledge

Mechanical 4.2
Computers and Electronics 3.9
Customer and Personal Service 3.9
English Language 3.6
Engineering and Technology 3.4
Mathematics 3.0

Abilities

Problem Sensitivity 3.8
Near Vision 3.8
Finger Dexterity 3.6
Deductive Reasoning 3.4
Written Comprehension 3.3
Inductive Reasoning 3.3
Information Ordering 3.3
Visualization 3.3
Arm-Hand Steadiness 3.3
Manual Dexterity 3.3
Oral Comprehension 3.1
Control Precision 3.1
Visual Color Discrimination 3.1
Oral Expression 3.0
Written Expression 3.0
Category Flexibility 3.0
Flexibility of Closure 3.0
Perceptual Speed 3.0
Selective Attention 3.0
Extent Flexibility 3.0

Essential skills

Reading Comprehension 3.1
Critical Thinking 3.1
Active Listening 3.0
Active Learning 3.0

Skills in demand

Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.

Tools & technology

Example Category
Microsoft Office software Office suite software Hot technology In demand
Microsoft Excel Spreadsheet software Hot technology
Microsoft Outlook Electronic mail software Hot technology
Microsoft PowerPoint Presentation software Hot technology
Microsoft Word Word processing software Hot technology
Salesforce software Customer relationship management CRM software Hot technology
SAP software Enterprise resource planning ERP software Hot technology
Inventory control system software Inventory management software In demand
Computerized maintenance management system CMMS Facilities management software
FaceTime Video conferencing software
Medical equipment diagnostic software Medical software
Web browser software Internet browser software

Work context

How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.

Importance of Being Exact or Accurate 4.7
Indoors, Environmentally Controlled 4.7
E-Mail 4.7
Face-to-Face Discussions with Individuals and Within Teams 4.7
Telephone Conversations 4.5
Contact With Others 4.4
Freedom to Make Decisions 4.3
Work With or Contribute to a Work Group or Team 4.3
Determine Tasks, Priorities and Goals 4.3
Impact of Decisions on Co-workers or Company Results 4.0
Frequency of Decision Making 3.9
Deal With External Customers or the Public in General 3.8
Time Pressure 3.8
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 3.8
Coordinate or Lead Others in Accomplishing Work Activities 3.8
In an Enclosed Vehicle or Operate Enclosed Equipment 3.6
Physical Proximity 3.5
Spend Time Standing 3.5
Consequence of Error 3.5
Health and Safety of Other Workers 3.4
Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 3.4
Importance of Repeating Same Tasks 3.3
Exposed to Hazardous Conditions 3.2
Exposed to Cramped Work Space, Awkward Positions 3.0
Level of Competition 3.0
Written Letters and Memos 3.0
Exposed to Contaminants 2.9
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 2.8
Indoors, Not Environmentally Controlled 2.7
Work Outcomes and Results of Other Workers 2.7
Spend Time Walking or Running 2.6
Spend Time Bending or Twisting Your Body 2.6
Exposed to Very Hot or Cold Temperatures 2.6
Exposed to Disease or Infections 2.5
Spend Time Making Repetitive Motions 2.5
Spend Time Kneeling, Crouching, Stooping, or Crawling 2.5
Outdoors, Exposed to All Weather Conditions 2.5
Exposed to Radiation 2.4
Spend Time Sitting 2.4
Exposed to Minor Burns, Cuts, Bites, or Stings 2.4

How to get in

Job zone
Zone 3 — Job Zone Three: Medium Preparation Needed
Education
Most occupations in this zone require training in vocational schools, related on-the-job experience, or an associate's degree.
Typical entry-level education
Associate's degree · BLS, the typical path — not a requirement
Related experience
Previous work-related skill, knowledge, or experience is required for these occupations. For example, an electrician must have completed three or four years of apprenticeship or several years of vocational training, and often must have passed a licensing exam, in order to perform the job.
Preparation level
SVP (6.0 to < 7.0) — total schooling plus on-the-job experience.

What to study: Engineering/Engineering-Related Technologies/Technicians . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.

Education of current workers

Share of people in this occupation at each level of education.

Associate's Degree (or other 2-year degree) 39.3%
High School Diploma 34.7%
Post-Secondary Certificate 13.3%
Some College Courses 12.7%

Interests & work styles

The interests and personal qualities O*NET associates with people who do this work.

Career interests (Holland / RIASEC)

Realistic 7.0
Conventional 4.8
Investigative 4.6
Social 2.0

Interest areas

Mechanics/Electronics 6.5
Engineering 5.4
Health Care Service 3.3
Physical/Manual Labor 2.8
Information Technology 2.6
Mathematics/Statistics 2.4
Medical Science 2.3
Physical Science 2.0

Work styles

Dependability 4.0
Attention to Detail 3.0
Cautiousness 2.5
Integrity 2.1

Wages & employment

U.S. · annual wages (BLS OEWS)

$39k10th$48k25th$63kMedian$79k75th$99k90th
Annual wages by percentile — U.S. (BLS OEWS). The light band spans the 10th–90th percentile; the darker band is the middle half (25th–75th); the line is the median.
68k202477k2034 (proj.)+12.9% · Growing fast
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for the occupation, not an AI-impact forecast.
10th percentile $39,060
25th percentile $48,100
Median (50th) $62,630
75th percentile $79,440
90th percentile $99,290
People employed 60,830

Industries that employ this occupation

Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.

Industry Workers National median pay
Wholesale Trade · Sector 21,540 $67,160
Health Care and Social Assistance · Sector 12,800 $65,980
Other Services (except Public Administration) · Sector 10,570 $62,250
Real Estate and Rental and Leasing · Sector 6,160 $42,650
Retail Trade · Sector 3,310 $45,180
Manufacturing · Sector 2,680 $62,860
Professional, Scientific, and Technical Services · Sector 1,270 $71,950
Management of Companies and Enterprises · Sector 1,060 $81,080
Administrative and Support and Waste Management and Remediation Services · Sector 280 $59,870
Educational Services · Sector 270 $66,280
Pharmacies and Drug Retailers · National industry 260 $45,020
Transportation and Warehousing · Sector 160 $63,790

Where this work is most concentrated

Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).

Industry Concentration Workers
Wholesale Trade · Sector 9.05× 21,540
Real Estate and Rental and Leasing · Sector 6.59× 6,160
Other Services (except Public Administration) · Sector 6.05× 10,570
Health Care and Social Assistance · Sector 1.4× 12,800
Management of Companies and Enterprises · Sector 0.96× 1,060
Pharmacies and Drug Retailers · National industry 0.93× 260
Retail Trade · Sector 0.54× 3,310
Manufacturing · Sector 0.53× 2,680

Part of the Advanced Manufacturing career cluster.

Exposure quadrant: AI task-overlap percentile vs Median pay Medical Equipment Repairers sits at the 44th percentile of AI task-overlap and the 51st percentile of median pay, placed here against 12 adjacent occupations on the same two axes. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Medical Equipment Repairers Medical Appliance Technicians Electrical and Electronics Installers and Repairers, Transportation Equipment Robotics Technicians Photonics Technicians Aerospace Engineering and Operations Technologists and Technicians Calibration Technologists and Technicians AI task-overlap percentile → ↑ Median pay
AI task-overlap percentile (horizontal) vs. median-pay percentile (vertical), across all scored occupations. This occupation is highlighted; related occupations are plotted alongside it. Overlap measures shared tasks with AI, not automation.

Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.

What you can do with this

Options the data surfaces for Medical Equipment Repairers — not advice or a forecast. Each is a real cross-link you can follow into the evidence.

Skills that travel

Capabilities this work builds that are used across many other occupations.

Adjacent roles

Occupations O*NET rates as related — the nearby moves on the map.

Paths in

How people typically prepare for this work.

Zoom out

On the global GenAI exposure gradient this work sits around the 37th percentile of 427 international occupations.

Write a report on thisheadline · factoids · citation

Medical Equipment Repairers show 44th-percentile AI task overlap — and about 7,300 annual U.S. openings

  • Medical Equipment Repairers rank in the 44th percentile (Moderate band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
  • The occupation is projected to see about 7,300 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
  • BLS projects employment to be growing fast (+12.9%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $62,630, across about 60,830 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Medical Equipment Repairers show 44th-percentile AI task overlap — and about 7,300 annual U.S. openings

• Medical Equipment Repairers rank in the 44th percentile (Moderate band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE)
• The occupation is projected to see about 7,300 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34)
• BLS projects employment to be growing fast (+12.9%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $62,630, across about 60,830 U.S. workers. (BLS OEWS (May 2024))

Source: Singulariki — "Medical Equipment Repairers". https://singulariki.com/roles/role-49-9062-00
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.

AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom

Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

Data compiled June 2, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Medical Equipment Repairers." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-49-9062-00

APA

Singulariki. (2026). Medical Equipment Repairers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-49-9062-00

BibTeX 
@misc{singulariki-role-49-9062-00,
  title  = {Medical Equipment Repairers},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
  url    = {https://singulariki.com/roles/role-49-9062-00}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.

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