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SOC 17-2131
On this page, materials engineers refers to O*NET 17-2131.00: workers who evaluate materials and develop machinery and processes to manufacture materials for products meeting specific design and performance specifications, and develop new uses for known materials, including titles such as metallurgical engineer, ceramic engineer, and welding engineer.
Model impact index for three equally weighted representative core tasks; not a measured share of working time or a job-loss probability. floor((50+75+50)/3+0.5)=58; fermatmind-ai-impact-v1; 2026-10-18.
The core work of materials engineers is to ensure materials meet product requirements within cost and performance constraints: conduct or supervise raw-material and finished-product tests to ensure quality; recommend materials against design goals such as strength, weight, heat resistance, conductivity, and cost; evaluate technical and economic factors in processes and product designs; plan laboratories and develop materials and manufacturing processes; analyze product failure data and test results to determine causes and propose solutions; determine manufacturing and joining methods; design and direct process tests; monitor material performance and deterioration; and reproduce material characteristics and train customers when needed.
The following judgments concern materials engineers' engineering and research practices. They do not predict hiring, registration, qualification, or contract outcomes.
Sample output and reflection: check whether design requirements and constraints were defined first, data sources and test conditions were explained, comparable material and process options were provided, and validation and failure-analysis boundaries were stated. Then ask yourself whether you can balance performance, processes, and cost, communicate across design, manufacturing, and quality teams, and take responsibility for material conclusions and consequences.
On this page, materials engineers refers to O*NET 17-2131.00: workers who evaluate materials and develop machinery and processes to manufacture materials for products meeting specific design and performance specifications, and develop new uses for known materials, including titles such as metallurgical engineer, ceramic engineer, and welding engineer. Tasks include testing raw materials and finished products, recommending materials against design goals, assessing technical and economic factors, planning laboratories and developing materials and manufacturing processes, analyzing failure data, determining manufacturing and joining methods, designing and directing process tests, monitoring material performance and deterioration, and reproducing material characteristics. Work mainly takes place in laboratories, factories, and offices. This page excludes adjacent roles such as architectural and engineering managers, biomedical engineers, chemical engineers, electrical engineers, and electronics engineers.
Career direction comparison
The following compares materials engineers with adjacent roles by actual subjects, core deliverables, and professional boundaries. Qualifications are not interchangeable based on titles.
| Career direction | Core work and output | Key differences | Best-fit choice |
|---|---|---|---|
| Architectural and Engineering Managers | Architectural and engineering managers oversee projects, teams, and budgets; materials engineers handle material selection, testing, and process development. Responsibilities differ. | Oversee projects, teams, and budgets. | Compare if you prefer engineering management. |
| Biomedical Engineers | Biomedical engineers work with medical and biological engineering; materials engineers work with materials and manufacturing processes. Medical materials require collaboration with biomedical engineering. | Work with medical and biological engineering. |
AI impact on this career
Editorial task hypothesis: distinguish materials simulation, machine learning for performance prediction, and generative AI. The latter may help organize fictional test records, literature summaries, or report drafts. No occupational adoption rates / job outcomes were obtained. Model output is not measured performance. People must verify original conditions, data, standards applicability, and citations. Do not upload formulations or client secrets without approval or release materials based on generated text. AI Impact Score 58% is an editorial estimate. Model impact index for three equally weighted representative core tasks; not a measured share of working time or a job-loss probability. floor((50+75+50)/3+0.5)=58; fermatmind-ai-impact-v1; 2026-10-18.The three tasks, ratings and sources are listed in the FermatMind method source record on this page.
FermatMind AI Impact Score estimation method v1
FermatMind / 费马测试 · 2026-10-18
Editorial ratings use the existing occupational responsibilities and AI task analysis on this page. They are not adoption rates, measured effects, job-disappearance or personal-unemployment probabilities, or official scores from Stanford or another external institution. No measured time weights or future robot deployment are assumed.
Chinese mainland salary reference
Scope: National Bureau of Statistics 2025 average annual wages for manufacturing employees are 113,594 yuan / year in urban non-private units and 76,055 yuan / year in urban private units; the nationwide total for urban non-private units is 129,441 yuan / year. All are industry measures, not this occupation's median or starting pay.
Category boundary: the Ministry of Human Resources and Social Security publishes enterprise compensation survey information by occupation / position, which can be used to look up materials and manufacturing pay. This page did not obtain an entry matching O*NET 17-2131.00 exactly, so it is not used as a nationwide occupational median. Refer to competent authority publications for specifics.
Only average annual wages are published
Only average annual wages are published
U.S. salary reference
The 2025 US median wage for 17-2131 is 112,860 dollars annually and 54.26 dollars hourly; full percentiles appear in the table. Older employment of 23,000 in 2024 and 1,500 average annual openings in 2024—2034 are separate. Latest figures are 23,800 employed in 2025, 8% growth in 2025—2035, and 1,300 average annual openings. Net growth and replacement openings differ; these are not individual hiring probabilities.
| Percentile | Annual reference | Hourly equivalent | Explanation |
|---|---|---|---|
| P10 | $72,300 / year | $34.76 / hour | 2025 US nationwide percentiles for occupation 17-2131, not seniority, starting pay, or a conversion of individual working hours. |
| P25 | $88,080 / year |
Fit signals
To assess fit, consider whether you can translate product requirements into material and test plans, rigorously analyze test and failure data, balance performance, processes, and cost, communicate across design, manufacturing, and quality teams, and keep learning materials and standards. Tools such as RIASEC can only propose hypotheses and cannot replace real task experience.
Positive signals： Positive signals: structured materials analysis, data- and test-based judgment, selection trade-offs under multiple constraints, communication and coordination across parties, and responsibility for conclusions and safety.
Reasons for caution： Reasons for caution: difficulty quantifying design requirements, skipping testing and data validation, unwillingness to communicate and advance work between laboratories and factories, or difficulty handling safety and compliance pressure.
Trial activity： Trial activity: using entirely fictional material performance data and failure examples, rehearse selection, evaluation, and failure analysis, and ask someone else to review them against the records.
Risks and boundaries
Handle risks by their triggers, consequences, controls, and escalation boundaries.
Based on O*NET 17-2131.00 tasks and work context and specific requirements concerning test conditions, selection and performance, process feasibility, safety exposure, and compliance boundaries. Check specific rules against employer procedures and applicable laws without extrapolating across scopes.
Typical scenario：Unreliable test conditions or data lead to misjudgment.
Roles most affected：Testing and analysis roles
Possible consequence：May lead to incorrect conclusions.
How to reduce risk：Check specimens / batches, test conditions, equipment status, units, and original data. Do not conclude when conditions are unclear. This is an editorial review action, not a specified standards provision.
Entry pathways
ONet's new-hire education survey reports 80% bachelor's, 8% doctorate, and 4% two-year / associate degree, not a uniform threshold. Years of preparation for JobZone4 is a group description. BLS says entry typically requires a materials or related engineering bachelor's; some research and development roles require a master's or doctorate. Entry does not require prior years of related work or a PE.
Market signals
Retain older employment of 23,000 in 2024 and 1,500 average annual openings in 2024—2034. Latest figures are 23,800 employed in 2025, 8% growth in 2025—2035, and 1,300 average annual openings, including replacements, not ten-year totals, net new jobs, or individual hiring probabilities.
US nationwide · Display scope: Materials Engineers (17-2131.00)
The main industries on that page for 2024 are Manufacturing and Professional, Scientific, and Technical Services. Employment and openings are statistical projections and must be interpreted separately from individual opportunities.
Employment size and change
Employment size, change, and job openings must be interpreted separately.
Does not establish：Occupational statistics cannot guarantee individual employment.
On this page, materials engineers refers to O*NET 17-2131.00: workers who evaluate materials and develop machinery and processes to manufacture materials for products meeting specific design and performance specifications, and develop new uses for known materials. Tasks include testing raw materials and finished products, recommending materials against design goals, evaluating technical and economic factors, planning laboratories and developing materials and processes, analyzing failure data, determining manufacturing and joining methods, and monitoring material performance and deterioration. Work mainly takes place in laboratories, factories, and offices. This occupation is distinct from architectural and engineering managers, biomedical engineers, chemical engineers, electrical engineers, or electronics engineers.
Choose a real task from this page for a small practice project or a conversation with someone in the field. Use the planning guides to set a date, an output and feedback questions before deciding whether to continue.
This is an entirely fictional material-selection scenario check, not a personality diagnosis, hiring conclusion, or qualification assessment.
Entirely fictional task package: provide fictional material performance data and failure examples, including 1 set of design requirements and selection constraints, 1 set of test data and failure observations, and 1 selection trade-off problem. Within 60 minutes, write testing and evaluation approaches, candidate materials and process options, failure-cause hypotheses and validation methods, and risks. Do not use real company, product, or classified data.
Check first: design requirements and performance indicators, test conditions and data scope, material and process constraints, cost and capacity limits, safety and compliance requirements, and evidence strength and authorization boundaries for conclusions.
End-to-end work: define design and performance requirements, collect data, evaluate selection and processes, conduct tests and failure analysis, propose improvements and validation, and support trial and mass production. Do not conclude before test conditions or data scope are confirmed, or put materials into use before safety and compliance boundaries are checked.
| Dimension | Primary track | Comparison track |
|---|---|---|
| Complete workflow | From defining requirements to supporting mass production | |
| Step one | Define design and performance requirements | |
| Step two | Collect material and test data | |
| Step three | Evaluate selection and process options | |
| Step four | Conduct testing and failure analysis | |
| Step five | Propose improvement and validation plans | |
| Step six | Support trial and mass production |
Inputs: design and performance requirements, materials and alloy systems, test and inspection equipment, process and joining methods, failure and deterioration data, cost and capacity constraints, regulatory and safety requirements, stakeholders, and project goals.
Checkable outputs: material selection and substitution recommendations, test plans and data conclusions, failure analyses and improvement options, process and joining methods, performance and deterioration assessments, technical reports and budget proposals, and training and material-transfer documentation.
Complete workflow: define design and performance requirements → collect material and test data → evaluate selection and process options → perform testing and failure analysis → propose improvement and validation plans → support trial and mass production.
In the United States, this occupation is in Job Zone 4. Most positions require a four-year bachelor's degree and typically several years of related experience. Welding, nondestructive testing, and special equipment conclusions must be issued by qualified personnel. This page does not judge individual eligibility.
Work subjects and AI boundaries for materials engineers Editorial task hypothesis: distinguish materials simulation, machine learning for performance prediction, and generative AI. The latter may help organize fictional test records, literature summaries, or report drafts. No occupational adoption rates / job outcomes were obtained. Model output is not measured performance. People must verify original conditions, data, standards applicability, and citations. Do not upload formulations or client secrets without approval or release materials based on generated text.
| Compare if you prefer medical engineering. |
| Chemical Engineers | Chemical engineers handle chemical processes and plants; materials engineers handle material performance, selection, and manufacturing processes. The roles overlap in material processing but have different goals. | Handle chemical processes and plants. | Compare if you prefer chemical processes. |
|---|
| Electrical Engineers | Electrical engineers handle electrical systems and equipment; materials engineers handle materials and processes. Conclusions on electrically functional materials require collaboration with electrical engineering. | Handle electrical systems and equipment. | Compare if you prefer electrical systems. |
|---|
First use a reviewable material deliverable to validate requirements definition, testing scope, and selection boundaries, then assess your direction. Do not assign a single ranking based on income or personality.
Next, turn the comparison into a small testing exercise that can be stopped.
Describe only specific steps tools may assist; do not treat demonstrations as organizational adoption.
Check data sources, system reliability, and review responsibilities; this page has no occupation-specific adoption rate.
Without occupational job-outcome research, do not infer layoff timing, staffing changes, or hiring probability.
| Work area | Task | Current change | Human control point |
|---|---|---|---|
| Testing and data | Conduct tests and analyze data | Editorial hypothesis: documentation may receive assistance. Specialized calculation and generative text capabilities differ; adoption or replacement has not been demonstrated. | Check test conditions and scope. |
| Selection and reports | Develop selection recommendations and write reports | May assist with drafting | Retain specimen / batch information, test conditions, and original results, and check model applicability and citations. Do not release unvalidated performance or sign beyond your authority; hand over instead. |
| Processes and validation | Determine processes and validate performance | No automated decisions | Confirmed by engineers and production leads. |
| Safety and compliance | Assess safety and compliance impacts | Cannot replace responsibility-based judgment | Confirmed by qualified personnel. |
Occupational sources describe actual tasks and subjects: materials and alloys, tests and equipment, processes and joining, failures and performance. Tool capabilities, organizational adoption, and job outcomes are recorded separately; wage or employment data is not used as AI evidence.
Editorial comparison: drafts may receive assistance, but no adoption-sequencing research was obtained. Traditional simulation / machine learning does not demonstrate generative AI adoption or product safety. Selection / failure causality requires experimental validation.
AI primarily changesMay assist with literature / report drafts; distinguish simulation, machine learning, and generative AI.
Human responsibility remainsCondition judgments and conclusions
AI primarily changesMay organize test descriptions; failure causality and safety performance require actual validation.
Human responsibility remainsTrade-offs and responsibility
Human control points: define design and performance requirements, judge test conditions and data reliability, balance performance, processes, and costs, take responsibility for failure conclusions and safety compliance, and follow engineering ethics and authorization boundaries.
Confirm requirements, test conditions, and compliance.
Analyze only within engineering and safety boundaries.
Review data, assumptions, and conclusions.
Promptly report safety and scope-boundary risks.
May lead to incorrect conclusions.
Control: Define conditions and review data.
May affect product reliability.
Control: Test to standards and assess margins.
May affect personnel safety.
Control: Implement protection and safety procedures.
Practice testing and data analysis fundamentals.
Retain supporting evidence for testing and selection.
Define test scope and safety boundaries first.
Task exposure, adoption, and job outcomes measure different things and cannot establish a date for job cuts.
Source: O*NET 17-2131.00 TasksOriginal source ↗
Only task hypotheses are listed; no adoption-sequencing or job-outcome research was obtained. People must verify actual tasks and authorization.
Source: O*NET 17-2131.00 TasksOriginal source ↗
There is no occupational adoption-rate source, so this page provides no such figures.
Source: O*NET 17-2131.00 Materials Engineers (Summary)Original source ↗
First conduct an offline exercise using entirely fictional material performance data and failure examples. Write testing and evaluation approaches, selection options, and validation boundaries without relying on unverified automated analysis to replace engineering judgment.
Insufficient evidence: not separately listed
Exact occupational wages were not obtained. Manufacturing-unit averages provide only manufacturing employer context, not occupational medians or individual business income.
| Role scope | Reference value | Explanation |
|---|---|---|
| Not separately tabulated | Hiring depends on the employer and position | National Bureau of Statistics wage statistics are organized by industry and registration type, not by education levels within this occupation. |
| Not separately tabulated | Hiring depends on the employer and position | National Bureau of Statistics wage statistics are organized by industry and registration type, not by education levels within this occupation. |
| Not separately tabulated | Hiring depends on the employer and position | National Bureau of Statistics wage statistics are organized by industry and registration type, not by education levels within this occupation. |
| Not separately tabulated | Hiring depends on the employer and position | National Bureau of Statistics wage statistics are organized by industry and registration type, not by education levels within this occupation. |
113,594 yuan / year
76,055 yuan / year
129,441 yuan / year
Insufficient evidence: no nationwide occupational median wage, reference period, or statistical scope was obtained for materials engineers in mainland China. This page displays only an industry proxy labeled as such; neither proxy figures nor US figures fill the gap.
| $42.35 / hour |
| 2025 US nationwide percentiles for occupation 17-2131, not seniority, starting pay, or a conversion of individual working hours. |
| P50 (median) | $112,860 / year | $54.26 / hour | 2025 US nationwide percentiles for occupation 17-2131, not seniority, starting pay, or a conversion of individual working hours. |
|---|
| P75 | $142,720 / year | $68.61 / hour | 2025 US nationwide percentiles for occupation 17-2131, not seniority, starting pay, or a conversion of individual working hours. |
|---|
| P90 | $175,720 / year | $84.48 / hour | 2025 US nationwide percentiles for occupation 17-2131, not seniority, starting pay, or a conversion of individual working hours. |
|---|
Wages · Median：$112,860 / year (2025)；O*NET 17-2131.00 National Wages (BLS OEWS Display)
Wages · Hourly median：$54.26 / hour (2025)；O*NET 17-2131.00 National Wages (BLS OEWS Display)
Wages · Lowest 10%：$72,300 / year (P10, 2025)；O*NET 17-2131.00 National Wages (BLS OEWS Display)
Wages · P90 percentile：$175,720 / year (P90, 2025)；O*NET 17-2131.00 National Wages (BLS OEWS Display)
Wages · Statistical scope：Materials Engineers（17-2131.00）；O*NET 17-2131.00 National Wages (BLS OEWS Display)
Full 2025 annual / hourly wage percentiles for occupation 17-2131, not seniority, starting pay, or take-home income.
Employment count in 2024, not the number of vacancies being recruited for.
Latest 2025—2035 growth is 8%, with 1,300 average annual openings. The older version is separate; these are not individual opportunities or net new jobs.
The industry table gives 2025 median annual wages for this occupation in each industry, not averages for all industry personnel or employment shares.
| Industry | Median annual wage (dollars / year) | How to interpret |
|---|---|---|
| Government, excluding state and local education and hospitals | $137,610 / year | May 2025, US occupation 17-2131; not a promise of individual income. |
| Natural sciences / engineering / life sciences research and development | $132,070 / year | May 2025, US occupation 17-2131; not a promise of individual income. |
| Transportation equipment manufacturing | $125,190 / year | May 2025, US occupation 17-2131; not a promise of individual income. |
| Engineering services | $124,950 / year | May 2025, US occupation 17-2131; not a promise of individual income. |
US entry typically requires a related engineering bachelor's, with some research roles requiring a master's or doctorate. PE is not required for entry; check state practice and task-specific qualifications separately.
Check evidence of testing / selection / failure-analysis processes and role conditions. No comparison of the hiring weights of work samples and certificates was obtained; paper work does not grant sign-off or equipment operating authority.
Strongly affected by manufacturing and professional-service distribution; do not extrapolate across regions.
Check with work samples rather than replacing judgment with labels.
The O*NET interest code is RIC (Realistic–Investigative–Conventional), emphasizing hands-on practice, research and analysis, and organizing information according to procedures. These labels describe activity preferences only and cannot determine competence or qualifications.
Do not use it this way: Hiring, qualifications, or performance cannot be inferred from this.
Start a career-interest trialCheck with work samples rather than replacing judgment with labels.
General personality measures such as the Big Five do not provide job evidence for this occupation and can only support self-reflection. Continue checking through real material testing, failure analysis, and selection communication experiences.
Do not use it this way: Hiring, qualifications, or performance cannot be inferred from this.
Start a career-interest trialCheck with work samples rather than replacing judgment with labels.
Type-based tools such as MBTI and the Enneagram cannot determine competence or qualifications and can only support self-reflection.
Do not use it this way: Hiring, qualifications, or performance cannot be inferred from this.
Start a career-interest trialCheck with work samples rather than replacing judgment with labels.
Continue checking against real tasks, boundaries, and reviewable deliverables.
Do not use it this way: Hiring, qualifications, or performance cannot be inferred from this.
Start a career-interest trialCheck with work samples rather than replacing judgment with labels.
Continue checking against real tasks, boundaries, and reviewable deliverables.
Do not use it this way: Hiring, qualifications, or performance cannot be inferred from this.
Start a career-interest trialCheck with work samples rather than replacing judgment with labels.
Continue checking against real tasks, boundaries, and reviewable deliverables.
Do not use it this way: Hiring, qualifications, or performance cannot be inferred from this.
Start a career-interest trialFits better when: Can design tests and analyze data.
Watch for: Conditions and scope must be checked.
Fits better when: Can recommend materials against goals.
Watch for: Performance and costs must be checked.
Fits better when: Can determine manufacturing and joining methods.
Watch for: Their feasibility must be checked.
Fits better when: Can analyze failures and propose improvements.
Watch for: Evidence strength must be stated.
Fits better when: Can assess safety and compliance.
Watch for: Applicable regulations must be checked.
Fits better when: Can collaborate with design, manufacturing, and quality teams.
Watch for: Multiple stakeholder needs must be handled.
Use this page's work sample to check plan design.
Check assumptions and evidence against methodological requirements.
Assess trade-off and judgment skills.
Check first and mark uncertainty.
Assess interdisciplinary collaboration skills.
Assess responsibility and engineering ethics awareness.
Use test and selection records to enable review by others.
Complete an exercise using entirely fictional material performance data and failure examples.
Evidence：O*NET 17-2131.00 Tasks
Typical scenario：Material selection or performance fails requirements.
Roles most affected：Selection and research roles
Possible consequence：May affect product reliability.
How to reduce risk：Test to standards and assess performance margins.
Evidence：O*NET 17-2131.00 Tasks
Typical scenario：Infeasible process or joining methods.
Roles most affected：Process and manufacturing roles
Possible consequence：May cause rework or failure.
How to reduce risk：Assess process feasibility and validation.
Evidence：O*NET 17-2131.00 Tasks
Typical scenario：Exposure to contaminants, hazardous conditions, and equipment.
Roles most affected：Laboratory and factory roles
Possible consequence：May affect personnel safety.
How to reduce risk：Applicable US laboratory hazardous chemical use follows written chemical hygiene plans, engineering controls, effective protective equipment, and training. Check factory production standards separately; laboratory provisions do not authorize every task.
Evidence：OSHA Laboratory Chemicals
Typical scenario：Issuing conclusions beyond engineering or authorization boundaries.
Roles most affected：Engineering judgment roles
Possible consequence：May violate engineering standards and responsibility requirements.
How to reduce risk：PE is not required for US entry. Public services / project sign-off and specific Chinese work categories require actual jurisdictional authorization. Material reports or degrees do not automatically confer every qualification.
Evidence：BLS Materials Engineer Practice Boundaries
Typical scenario：Rushing to conclusions with limited failure data.
Roles most affected：Analysis and improvement roles
Possible consequence：May mislead improvement decisions.
How to reduce risk：Add tests and state evidence strength.
Evidence：O*NET 17-2131.00 Tasks
Typical scope：Entry stage: practice materials and testing fundamentals, data recording and analysis, basic failure observation, learning processes and standards, and documentation under supervision. Learn safety and compliance requirements and retain process records.
Readiness evidence：Evidence to show: use a reviewable material or process deliverable covering requirements definition, test conditions, data conclusions, and selection recommendations to demonstrate structured engineering analysis and accurate documentation.
Credential boundary：Verify education and practical requirements.
Next moves：Next step: check the target employer's material systems and processes, standards and compliance requirements, and testing and inspection conditions. Validate testing, analysis, and selection abilities through real projects under supervision.
Typical scope：Independently test, select, and evaluate, with work subject to review.
Readiness evidence：Retain test and selection records.
Credential boundary：Verify employer requirements.
Next moves：Moving toward greater responsibility: with experience, workers may oversee end-to-end material or process development, train newcomers and establish systematic methods, or move into research and development management, quality, and process engineering.
Typical scope：Handle complex materials and interdisciplinary solutions.
Readiness evidence：Retain complex-project and validation records.
Credential boundary：Verify employer requirements.
Next moves：Add complex-project and training evidence.
Typical scope：Oversee technical direction and teams.
Readiness evidence：Retain technical-direction and team records.
Credential boundary：Verify employer requirements.
Next moves：Add technical and management evidence.
Typical scope：Participate in process and quality work under supervision.
Readiness evidence：Retain process and quality records.
Credential boundary：Verify employer requirements.
Next moves：Add process and quality methods.
Typical scope：Independently handle process or quality improvements.
Readiness evidence：Retain improvement and validation records.
Credential boundary：Verify employer requirements.
Next moves：Add evidence of systematic methods.
Typical scope：Handle complex processes and quality systems.
Readiness evidence：Retain system and audit records.
Credential boundary：Verify employer requirements.
Next moves：Add system and audit evidence.
Typical scope：Oversee teams and standards.
Readiness evidence：Retain team and standards records.
Credential boundary：Verify employer requirements.
Next moves：Add governance evidence.
Typical scope：Participate in inspection and testing under supervision.
Readiness evidence：Retain testing records.
Credential boundary：Verify project and qualification requirements.
Next moves：Add testing methods and standards.
Typical scope：Independently handle testing or compliance tasks.
Readiness evidence：Retain testing and compliance records.
Credential boundary：Verify qualification requirements.
Next moves：Add qualification and compliance evidence.
Typical scope：Oversee standards and systems.
Readiness evidence：Retain standards and system records.
Credential boundary：Verify qualification requirements.
Next moves：Add system and governance evidence.
Typical scope：Oversee laboratory and compliance teams.
Readiness evidence：Retain laboratory and team records.
Credential boundary：Verify qualification requirements.
Next moves：Add management and credential evidence.
Confirm requirements, test conditions, and compliance.
Test, analyze, and validate according to standards.
Produce reviewable test and selection records.
Expand material and process responsibilities within authorized scope.
US nationwide · Display scope: Materials Engineers (17-2131.00)
About 1,500 openings / year (older version)
Projected average annual job openings
Older 2024—2034 annual average; the newer 2025—2035 annual average of 1,300 is listed separately, not a period total / net growth.
Does not establish：Cannot represent an individual's probability of being hired.
US nationwide · Display scope: Materials Engineers (17-2131.00)
$112,860 / year
Median annual wage
The BLS 2025 OEWS nationwide median, not starting pay or take-home income.
Does not establish：Full 2025 wage percentiles were obtained for occupation 17-2131; they do not represent individual income or seniority.
These are capability relationships, not automatic promotions or credential waivers.
Transfers：Transferable capabilities: material and test analysis, failure analysis and root-cause judgments, process and joining methods, data and standards interpretation, cost and performance trade-offs, interdisciplinary communication, and project management.
Build next：First target, architectural and engineering manager: add research and development / project planning, personnel and equipment allocation, budgets, hiring and team leadership, and quality and schedule coordination. Technical competence in material testing does not automatically demonstrate management responsibility or authorization across engineering disciplines. Build real resource and team deliverables for the target role.
View career profileTransfers：Engineering analysis foundations.
Build next：Add medical and biological knowledge.
View career profileTransfers：Foundation in materials and processes.
Build next：Add chemical process skills.
View career profileTransfers：Foundation in engineering and systems.
Build next：Develop deeper electrical design skills.
View career profileTransfers：Foundation in engineering and systems.
Build next：Develop deeper electronic design skills.
View career profileTransfers：Foundation in mechanics and materials.
Build next：Develop deeper mechanical design skills.
View career profileArchitectural and engineering managers oversee projects and teams; biomedical engineers work with medical engineering; chemical engineers handle chemical processes; electrical and electronics engineers handle electrical and electronic systems. Materials engineers handle material performance, selection, and manufacturing processes. Compare subjects, goals, and professional boundaries to distinguish them.
Observable signals: structured materials analysis, data- and test-based judgment, selection trade-offs under multiple constraints, communication and coordination across parties, and responsibility for conclusions and safety. O*NET interest code RIC describes activity preferences only and cannot determine competence or qualifications.
Tools for material performance modeling and simulation, test-data processing and failure-pattern recognition, literature and standards retrieval, and report generation may assist data analysis, performance prediction, and drafting. Engineers remain responsible for defining design requirements, judging test conditions, selection trade-offs, safety and compliance conclusions, and accountability. This page presents tool uses only as task hypotheses, not evidence of widespread organizational adoption.
Human responsibilities include defining design and performance requirements, judging test conditions and data reliability, balancing performance, processes, and cost, taking responsibility for failure conclusions and safety compliance, and following engineering ethics and authorization boundaries.
The National Bureau of Statistics publishes average annual wages for urban-unit employees by industry category without separately listing this occupation, so a safely matched nationwide occupational median cannot be established. This page displays only industry proxies labeled as such: in 2025, manufacturing paid 113,594 yuan / year in urban non-private units and 76,055 yuan / year in urban private units, while the nationwide total for urban non-private units was 129,441 yuan / year. None equals this occupation's median or starting pay. The Ministry of Human Resources and Social Security's enterprise compensation survey information is provided as a lookup entry point.
The O*NET page displays a 2025 BLS OEWS median annual wage of 112,860 dollars, approximately 54.26 dollars / hour, for occupation 17-2131.00. That page does not display percentile wages. These are US nationwide statistics, not individual take-home income or starting pay.
In the United States, this occupation is in Job Zone 4. Most positions require a four-year bachelor's degree, some require a doctorate, and several years of related experience are typically needed. Welding, nondestructive testing, and special equipment conclusions must be issued by qualified personnel. Mainland China: there is no unified occupational qualification exactly corresponding to this O*NET occupation; check employer and industry requirements.
Main risks include test conditions and data reliability, material selection and performance, process and joining feasibility, safety and hazardous-condition exposure, and conclusion authorization and compliance boundaries. Controls include defining test conditions and scope, standards-based testing and validation, process and safety assessment, and handing matters beyond scope to qualified personnel. Check specific rules against employer procedures and applicable laws.
O*NET cites BLS data showing about 23,000 employed in this occupation in 2024, projected above-average growth of 5% to 6% in 2024—2034, and about 1,500 job openings during the period. This small occupation is sensitive to numerical fluctuations. These are occupational statistics, not an individual's probability of being hired.
If you can translate product requirements into material and test plans and validate them with data, a low-cost exercise using entirely fictional material performance data and failure examples is worthwhile. Moving into chemical engineering, biomedical engineering, or research and development management requires additional corresponding expertise and qualification evidence.
Evidence for China, the United States, and individual organizations is presented separately. Conclusions on wages, employment, qualifications / credentials, safety, and AI must not be combined across scopes. The materials engineers page provides occupational judgment and engineering exercise information and does not replace local laws, engineering standards, safety requirements, or other professional advice. Any statement of insufficient evidence means only that safely matched data was not established within a bounded search; proxies or memory are not used to fabricate figures.
FermatMind research workflow
2025 BLS OEWS wage data; accessed 2026-09-25
O*NET 17-2131.00 National Wages (BLS OEWS Display)
Limitations：Applies only to 17-2131.00 and the US market; does not establish a mapping to China.
Limitations：Task examples do not mean every position performs every task; they do not establish a mapping to China.
Limitations：US work context does not replace Chinese law or employer procedures.
Limitations：This page does not display percentile wages; the median does not represent starting pay or individual take-home income.
Limitations：Projections are not a hiring guarantee; above average does not mean individual opportunities necessarily increase.
Limitations：Industry distribution signals employer settings, not projected growth or demand.
Limitations：Education distribution does not establish a mandatory requirement for every employer; it does not establish a mapping to China.
Limitations：Certification and training do not equal a scope of practice or employer hiring; check the applicable jurisdiction.
Limitations：Task exposure does not equal implemented automation, adoption, or layoffs; individual outcomes are not inferred.
Limitations：Industry averages are not occupational medians and exclude individually owned businesses and freelancers; no nationwide wage distribution matching the exact occupation was established.
Limitations：Covers urban enterprises, excluding government agencies and public institutions; this page did not obtain an exact occupational match and does not use it as a nationwide median.
Limitations：An editorial scale is not evidence of adoption rates, layoffs, regulations, or licensing.
Limitations：This US occupation; check state sign-off requirements and Chinese equivalents separately.
Limitations：Does not cover industrial production outside the laboratory-use definition; not Chinese law or an occupational accident rate.
Limitations：Editorial ratings use the existing occupational responsibilities and AI task analysis on this page. They are not adoption rates, measured effects, job-disappearance or personal-unemployment probabilities, or official scores from Stanford or another external institution. No measured time weights or future robot deployment are assumed.
Source scope, limitations, and statistical periods are checked separately against the original evidence. Source use notes: O*NET 17-2131.00 Materials Engineers (Summary): Provides the occupational identity, official description, interest code, Job Zone, skills, and knowledge for 17-2131.00.; The wage and employment data on that page cover this occupation.; O*NET 17-2131.00 Tasks: Provides a task list including testing raw materials and finished products, recommending material choices based on design objectives, evaluating technical and economic factors, planning laboratories and developing materials and processes, analyzing failure data, determining manufacturing and joining methods, and monitoring material performance.; The task sample does not mean every position performs every task.; O*NET 17-2131.00 Work Context: Describes settings that are primarily controlled indoor environments, daily communication by email and meetings, an emphasis on precision, and possible exposure to contaminants, hazardous conditions, and equipment.; U.S. work context does not replace Chinese law or employer procedures.; O*NET 17-2131.00 National Wages (BLS OEWS display): Median wage from 2025 BLS OEWS; the page covers this occupation.; Percentile wages are not displayed on this page.; O*NET 17-2131.00 National Employment Trends: Employment size in 2024, growth in 2024–2034 (faster than average at 5%–6%), and projected job openings.; Projections are not hiring guarantees.; Industries: 17-2131.00: The main industries on this page for 2024 are Manufacturing and Professional, Scientific, and Technical Services.; Industry distribution signals employer settings, not projected growth or demand.; O*NET 17-2131.00 Education and Career Preparation: Job Zone 4: Most positions require a four-year bachelor's degree (about 80%), while some require a doctorate (about 8%) or a two-year degree.; The education distribution does not constitute a mandatory requirement for every employer.; Licenses & Certifications: 17-2131.00: State licensing and national certification search tools provided by O*NET.; Certification and training do not equal authorization to practice or employer hiring requirements.; Generative AI and Jobs (ILO Working Paper 140, 2025): Assesses occupational exposure to generative AI at the task level.; The exposure index does not equal adoption rates, job outcomes, or hiring probabilities.; Average Annual Wages of Persons Employed in Urban Units in 2025: Provides average annual wages by broad industry category for urban non-private and private units, including manufacturing.; An industry average is not an occupational median and excludes individual businesses and freelancers.; FermatMind Materials Engineers Task Impact Scale: Organizes tasks that can be assisted and points requiring human control for task-level discussions of AI and fit.; This editorial scale is not evidence of adoption rates, layoffs, regulations, or licensing.;
