Automated Cutting Machine Operator
Role lens
Automated cutting machine operators send files from the computer to the cutting machine, place the material to be cut and digitize and select the fault in the materials surface in order to perform the nesting of the parts, unless the machine makes it automatically. They give the order to the machine to cut, collect the cut pieces and do the final quality control analysis against specifications and quality requirements. They also monitor the status of the cutting machine working devices.
As an automated cutting machine operator, you'll be responsible for preparing materials and operating sophisticated cutting equipment to produce precise components. Your work involves transferring digital designs to the machine, carefully positioning materials, and monitoring the cutting process to ensure accuracy and quality. You'll play a crucial role in manufacturing processes across various industries.
- • Transfer digital files to automated cutting machines and initiate cutting programs.
- • Prepare and position materials for cutting, including identifying and compensating for surface imperfections.
- • Monitor machine operation, identify and address any issues, and perform routine maintenance checks.
Where this occupation is in demand
Reported labour shortages and surpluses, by year. Published for occupation groups, not for individual job titles.
Figures cover Stationary plant and machine operators — 259 jobs including this one.
In shortage: Bulgaria, Italy, Portugal, Slovenia.
Longest-running shortage: Italy, 3 years.
Select a place on the map to see its figures.
About this source›
Source: ELA/EURES labour shortages and surpluses. Readings are published at occupation-group level, and cover Europe. Editions differ in annex layout and country coverage, so a change between years does not always mean the labour market changed. Countries in grey were not reported, which is not the same as being in balance.
What these words mean
The four things this section reports
- Reported demand
- Whether employers report needing people in this job — a judgement published by a national or EU body, not a count.
- Where it is heading
- Which way employment in this job is expected to move over the coming years, from an official projection.
- Openings
- Roughly how many openings arise — from growth and from people leaving the job.
- Typical pay
- What people in this job typically earn where the source publishes it. Blank does not mean unpaid; it means nobody publishes it for that place.
A measure is left out when nobody publishes it for that place, rather than shown as zero.
Which way the market leans for you
- In your favour
- More openings than people looking — employers are competing for candidates.
- Balanced
- Openings and candidates are roughly matched.
- Competitive
- More people looking than openings — expect to compete.
- Mixed evidence
- Sources disagree, or the same occupation group is short in one part and oversupplied in another.
Every source resolves to one of these four, so there is a single vocabulary to learn. What differs is the evidence behind it, which is printed underneath each verdict — a measured ratio of openings to jobseekers, or an assessment published by a national body.
How this job compares with other jobs in the same country
- Strong
- Among the strongest in that country
- Good
- Stronger than most jobs in that country
- Mixed
- About typical for that country
- Weak
- Weaker than most jobs in that country
This is a rank within one country, not a score you can carry across borders — the registers behind two countries count different people, so the same number means different things in each. It is also why a job can be among the strongest in a country and still show as Competitive: it leads the field in a market that is crowded overall.
Where these come from
Every figure is published by a national statistics office, a public employment service or an EU body, and each card names its source and the period it covers. Some places are counted monthly, others assessed once or twice a year, so two places on the same map can be describing different moments — the date is always shown.
None of this predicts one person’s chances. It describes a market.
Reported demand · Typical pay · Where it is heading (United States, Ireland, Australia)
| Reported demand | Typical pay | Where it is heading | |
|---|---|---|---|
| United States | Not reported | $46,570 2025-05 | −2.3% 2024–2034 · BLS 2024-2034 |
| Ireland | Not reported | — | +42.9% 2023–2035 · Cedefop 2026 * |
| Australia | Assessed as balanced Jobs and Skills Australia 2025 * | — | — |
* Published for occupation groups, not for individual job titles.
U.S. Bureau of Labor Statistics (OEWS)
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Future Outlook for automated cutting machine operator
The outlook for automated cutting machine operator reflects a balanced mix of automation exposure and durable, human-led work.
How are these scores calculated?
The Resilience Score (0–100) estimates how structurally protected this occupation is from automation and AI disruption, based on task-level analysis. Higher scores mean more human-judgment-intensive tasks. AI Exposure shows the estimated percentage of task hours that current AI capabilities could affect. These are model-derived structural indicators, not predictions about individual job security.
How could automated cutting machine operator change as AI adoption grows?
This role is likely to change gradually, with AI supporting selected tasks rather than replacing the whole occupation.
Illustrative scenario based on task automatability — not a forecast. Values are rounded the further ahead you look.
This role is likely to change gradually, with AI supporting selected tasks rather than replacing the whole occupation.
Illustrative scenario based on task automatability — not a forecast. Values are rounded the further ahead you look.
Model-based estimate. Use it as a planning signal, not a guarantee.
Compare this to your profile
How AI may change this role
Deterministic, model-based interpretation of current role signals — not a guarantee of replacement.
What still depends on people
Most tasks here are AI-assistable rather than purely human-led.
Where AI may become a co-pilot
- apply basic rules of maintenance to leather goods and footwear machinery
- operate automatic cutting systems for footwear and leather goods
- use pattern-cutting softwares
Tasks most exposed to automation
- use IT tools
Vital Signs & AI Vectors
AI Exposure Vectors
0-100%Exposure to physical automation, robotics, and sensor-driven task displacement
Exposure to AI-assisted analysis, pattern recognition, and predictive modelling tasks
Exposure to content generation, creative augmentation, and large language model tools
Exposure to workflow automation, decision-support software, and process digitisation
Technical Details
NexFuture v3.0 estimates automation exposure natively from ESCO essential-skill groups, weighted by skill mass and calibrated against expert anchors. Scores are probabilistic estimates, not guarantees. See the NexFuture Methodology White Paper for full details.
Measures automation exposure. It does not measure pay, demand, or how many jobs exist near you.
What people in this role usually do
Advanced Manufacturing
A typical day as an automated cutting machine operator
09 09:00 · Morning operate automatic cutting systems for footwear and leather goods
10 10:30 · Mid-morning apply basic rules of maintenance to leather goods and footwear machinery
12 12:00 · Midday use pattern-cutting softwares
14 14:00 · Afternoon use IT tools
Task order is illustrative. Individual days vary.
What you need to do this work
The skills, knowledge and tools this role calls for — and the traits and rewards that come with it.
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apply basic rules of maintenance to leather goods and footwear machinery
Apply basic rules of maintenance and cleanliness on footwear and leather goods production equipment and machines that you operate.
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operate automatic cutting systems for footwear and leather goods
Work with the equipment's software. Digitise and mark the leather areas with faults in order to avoid them. Establish nesting and cutting restrictions for each pattern. Pick up, sort, upload patterns, check and complete cutting orders. Adjust the machines and equipment parameters and perform simple procedures for maintenance.
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use pattern-cutting softwares
Use pattern-cutting softwares in order to create templates for the manufacturing of wearing apparel, made-up textile articles, and textile products. Set adequate patterns in softwares for replicability of products taking into account sizes and shapes.
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use IT tools
Application of computers, computer networks and other information technologies and equipment to storing, retrieving, transmitting and manipulating data, in the context of a business or enterprise.
automatic cutting systems for footwear and leather goods
The use and description of automatic systems technologies used in footwear and leather goods industry such as laser cutting, knife cutting, punch cutting, mill cutting, ultra-sound cutting, water jet cutting and the cutting machinery such as swing beam cutting presses, traveling head die cutting presses or strap cutting machines.
footwear components
Footwear components both for uppers (vamps, quarters, linings, stiffeners, toe puffs etc.) and bottoms (soles, heels, insoles etc.). Ecological concerns and the importance of recycling. Selection of suitable materials and components based on their influence on the footwear style and characteristics, properties and manufacturability. Procedures and methods in chemical and mechanical processing of leather and non-leather materials.
footwear equipments
Functionality of the wide range of equipments and the basic rules of regular maintenance.
footwear machinery
The functionality of the wide range of footwear machines, and the basic rules of regular maintenance.
footwear manufacturing technology
Footwear processes technology and machinery involved. The footwear manufacturing starts in the cutting/clicking room , cutting the uppers and bottom components. The upper components are joined together in the closing room by following a precise order of specific operations: skiving, folding, sewing etc. The closed upper, the insole and other bottom components are brought together in the assembling room, where the main operations are lasting and soling. The process ends with finishing operations in the finishing and packing room.
footwear materials
The characteristics, components, advantages and limitations of a wide range of materials used in footwear production: leather, leather substitutes (synthetics or artificial materials), textile, plastic, rubber etc.
footwear quality
Quality specifications of materials, processes and final products, the most common defects in footwear, quick tests procedures, laboratory tests procedures and standards, adequate equipment for quality checks. Quality assurance of footwear production processes and fundamental concepts on quality including footwear quality framework and standards.
leather goods components
The various procedures and methods in the processing of leather materials and leather goods components like manufacturability and properties.
leather goods manufacturing processes
The processes, technology and machinery involved in the leather goods manufacturing.
leather goods materials
The wide range of materials used in leather goods production: leather, leather substitutes (synthetics or artificial materials), textile, etc; the way of distinguishing among various materials based on their properties, advantages and limitations.
leather goods quality
The quality specifications of materials, processes, and final products, the most common defects in leather, quick tests procedures, laboratory tests procedures and standards, and the adequate equipment for quality checks.
manual cutting processes for leather
Cutting rules, variance of the leather properties on its surface and elongation directions of the footwear pieces.
Path to become an automated cutting machine operator
What it typically takes to qualify: education level, where it is a regulated profession, and where to study.
Upper secondary education
65 programmes in 18 countries teach the core skills of this job. Plus 13 short courses that build single skills.
A few examples, taught in the language of this page:
Ammattiopisto Tavastia · Finland
These are 6 of 78.
Sources
- 1. Source: Opintopolku.fi (Finnish National Agency for Education)
- 2. Source: U.S. Department of Education, College Scorecard (collegescorecard.ed.gov), CC BY. Data as at 10/06/2026. Adapted by NexPath.
- 3. Source: Kenya Universities and Colleges Central Placement Service (students.kuccps.ac.ke).
- 4. Source: Study in Korea, National Institute for International Education (NIIED) (studyinkorea.go.kr).
- 5. Source: YÖK Atlas, Council of Higher Education (yokatlas.yok.gov.tr).
- 6. Contains information from MySkillsFuture Course Run accessed on 2026-09-28 from data.gov.sg which is made available under the terms of the Singapore Open Data Licence version 1.0 (https://data.gov.sg/open-data-licence)
Growth Pathways & Similar Roles
Explore typical career progression paths, adjacent skills, and similar roles to plan your next transition.
Where does automated cutting machine operator fit?
Similarity scores based on skill overlap from ESCO data.
For organisations
The data on this page, working for your students, clients and staff.
Frequently asked questions
What kind of materials do automated cutting machine operators typically work with?
Do I need a background in computer programming to be an automated cutting machine operator?
What skills are important for success in this role?
Is there a shortage of Automated Cutting Machine Operator in Europe?
How much does Automated Cutting Machine Operator pay in the United States?
Sources: ESCO O*NET ELA/EURES Cedefop BLS Data updated October 3, 2026 About our data