Skills it runs on
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Materials Engineers
Occupation · SOC 17-2131.00
Evaluate materials and develop machinery and processes to manufacture materials for use in products that must meet specialized design and performance specifications. Develop new uses for known materials. Includes those engineers working with composite materials or specializing in one type of material, such as graphite, metal and metal alloys, ceramics and glass, plastics and polymers, and naturally occurring materials. Includes metallurgists and metallurgical engineers, ceramic engineers, and welding engineers.
Also called: Materials Engineer · Materials Research Engineer · Metallurgical Engineer · Metallurgist · Extrusion Engineer · Materials Development Engineer · Research Engineer · Test Engineer · Automotive Sheet Metal Engineer · Ceramic Design Engineer · Ceramic Engineer · Ceramic Research Engineer
Job family: Architecture and Engineering Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-17-2131-00/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.
Market signal
Independent published positions, read together — not a forecast.
- About average employment outlook (+5.7% by 2034)
- 1,500 openings/yr
- Moderate AI exposure
- Median pay $108,310/yr
- Work is mostly on-site (not teleworkable)
- A reversal from 2013 — rated low automation risk then (15th), high AI task-overlap now (69th)
69th-percentile task overlap — yet about 1,500 openings a year (+5.7% 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.) High | 76th | 1.0 | |
| LLM task exposure, γ (OpenAI / Eloundou) High | 69th | 0.8 | |
| AI assistant applicability (Microsoft) Moderate | 62nd | 0.2 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.5), and including AI-powered software (γ 0.8). 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 0.0 · 15th percentile among occupations · Low
Job outlook
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | About average · +5.7% by 2034 |
| Projected annual openings | 1,500 |
| Employment 2024 → 2034 | 23,000 → 24,300 |
“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 2 occupations below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
Materials Engineers sits at the 56th percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure rose from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
30% mean task exposure (2025)
56th percentile of 427 placed occupations
+5 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Engineering Professionals Not Elsewhere Classified · 2149 | 30% | Not exposed |
| Mining Engineers, Metallurgists and Related Professionals · 2146 | 29% | 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 21 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Analyze product failure data and laboratory test results to determine causes of problems and develop solutions. Core · importance 4.3
- Design and direct the testing or control of processing procedures. Core · importance 4.2
- Monitor material performance, and evaluate its deterioration. Core · importance 4.2
- Conduct or supervise tests on raw materials or finished products to ensure their quality. Core · importance 4.1
- Evaluate technical specifications and economic factors relating to process or product design objectives. Core · importance 4.1
- Modify properties of metal alloys, using thermal and mechanical treatments. Core · importance 4.1
- Determine appropriate methods for fabricating and joining materials. Core · importance 4.0
- Guide technical staff in developing materials for specific uses in projected products or devices. Core · importance 4.0
- Review new product plans, and make recommendations for material selection, based on design objectives such as strength, weight, heat resistance, electrical conductivity, and cost. Core · importance 4.0
- Supervise the work of technologists, technicians, and other engineers and scientists. Core · importance 3.9
- Plan and implement laboratory operations to develop material and fabrication procedures that meet cost, product specification, and performance standards. Core · importance 3.9
- Plan and evaluate new projects, consulting with other engineers and corporate executives, as necessary. Core · importance 3.8
- Supervise production and testing processes in industrial settings, such as metal refining facilities, smelting or foundry operations, or nonmetallic materials production operations. Core · importance 3.8
- Solve problems in a number of engineering fields, such as mechanical, chemical, electrical, civil, nuclear, and aerospace. Core · importance 3.6
- Conduct training sessions on new material products, applications, or manufacturing methods for customers and their employees. Core · importance 3.6
- Perform managerial functions, such as preparing proposals and budgets, analyzing labor costs, and writing reports. Core · importance 3.5
- Teach in colleges and universities. Supplemental · importance 3.4
- Present technical information at conferences. Core · importance 3.4
- Replicate the characteristics of materials and their components, using computers. Core · importance 3.2
- Design processing plants and equipment. Core · importance 3.2
- Write for technical magazines, journals, and trade association publications. Core · importance 3.2
Work activities
- Present research results to others.
- Conduct quantitative failure analyses of operational data.
- Monitor the productivity or efficiency of industrial operations.
- Supervise engineering or other technical personnel.
- Direct quality control activities.
- Evaluate technical data to determine effect on designs or plans.
- Test characteristics of materials or structures.
- Prepare proposal documents.
- Prepare operational reports.
- Prepare project budgets.
- Resolve operational performance problems.
- Evaluate plans or specifications to determine technological or environmental implications.
- Prepare detailed work plans.
- Confer with technical personnel to prepare designs or operational plans.
- Recommend technical design or process changes to improve efficiency, quality, or performance.
- Design industrial processing systems.
- Prepare materials for processing.
- Direct design or development activities.
- Determine operational methods.
- Train personnel on proper operational procedures.
- Direct industrial production activities.
- Write articles, books or other original materials in area of expertise.
- Create models of engineering designs or methods.
- Teach classes in area of specialization.
- Teach social science courses at the college level.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Engineering and Technology | 4.3 | |
| Chemistry | 4.3 | |
| Physics | 4.2 | |
| Production and Processing | 4.1 | |
| Mathematics | 4.1 | |
| English Language | 3.9 | |
| Design | 3.6 | |
| Computers and Electronics | 3.4 |
Essential skills
| Reading Comprehension | 4.0 | |
| Active Listening | 4.0 | |
| Science | 4.0 | |
| Critical Thinking | 3.9 | |
| Writing | 3.8 | |
| Speaking | 3.8 | |
| Mathematics | 3.8 | |
| Active Learning | 3.3 | |
| Monitoring | 3.1 |
Transferable skills
| Complex Problem Solving | 4.0 | |
| Judgment and Decision Making | 3.3 | |
| Instructing | 3.1 | |
| Service Orientation | 3.1 | |
| Operations Analysis | 3.1 |
Abilities
| Oral Comprehension | 4.0 | |
| Written Comprehension | 4.0 | |
| Oral Expression | 4.0 | |
| Deductive Reasoning | 4.0 | |
| Inductive Reasoning | 4.0 | |
| Category Flexibility | 4.0 | |
| Written Expression | 3.9 | |
| Problem Sensitivity | 3.9 | |
| Information Ordering | 3.8 | |
| Mathematical Reasoning | 3.8 | |
| Near Vision | 3.8 | |
| Fluency of Ideas | 3.5 | |
| Originality | 3.4 | |
| Flexibility of Closure | 3.3 | |
| Perceptual Speed | 3.3 | |
| Visualization | 3.3 | |
| Speech Recognition | 3.3 | |
| Speech Clarity | 3.3 |
Skills in demand
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Showing the top 40 of 43.
Tools & technology
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.
How to get in
- Job zone
- Zone 4 — Job Zone Four: Considerable Preparation Needed
- Education
- Most of these occupations require a four-year bachelor's degree, but some do not.
- Typical entry-level education
- Bachelor's degree · BLS, the typical path — not a requirement
- Related experience
- A considerable amount of work-related skill, knowledge, or experience is needed for these occupations. For example, an accountant must complete four years of college and work for several years in accounting to be considered qualified.
- Preparation level
- SVP (7.0 to < 8.0) — total schooling plus on-the-job experience.
What to study: Engineering . 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.
| Bachelor's Degree | 47.6% | |
| Doctoral Degree | 33.3% | |
| Master's Degree | 9.5% | |
| Post-Baccalaureate Certificate | 4.8% | |
| Post-Doctoral Training | 4.8% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Interest areas
| Engineering | 6.4 | |
| Physical Science | 6.0 | |
| Mathematics/Statistics | 4.2 | |
| Mechanics/Electronics | 3.8 | |
| Management/Administration | 2.9 | |
| Information Technology | 2.4 | |
| Public Speaking | 2.2 |
Work styles
| Dependability | 6.0 | |
| Attention to Detail | 5.0 | |
| Cautiousness | 4.0 | |
| Intellectual Curiosity | 3.0 | |
| Innovation | 2.5 |
Career interests (Holland / RIASEC)
| Realistic | 5.9 | |
| Investigative | 5.8 | |
| Conventional | 4.1 | |
| Artistic | 2.5 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $68,040 |
| 25th percentile | $85,820 |
| Median (50th) | $108,310 |
| 75th percentile | $138,370 |
| 90th percentile | $172,000 |
| People employed | 22,770 |
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 |
|---|---|---|
| Manufacturing · Sector | 11,970 | $105,920 |
| Professional, Scientific, and Technical Services · Sector | 5,590 | $108,630 |
| Engineering Services · National industry | 2,410 | $105,590 |
| Management of Companies and Enterprises · Sector | 1,570 | $113,870 |
| Testing Laboratories and Services · National industry | 560 | $88,660 |
| Wholesale Trade · Sector | 530 | $105,090 |
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 370 | $107,470 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 330 | $123,250 |
| Educational Services · Sector | 320 | $64,360 |
| Temporary Help Services · National industry | 280 | $118,430 |
| Construction · Sector | 160 | $83,040 |
| Utilities · Sector | 100 | $95,350 |
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 |
|---|---|---|
| Testing Laboratories and Services · National industry | 22.25× | 560 |
| Engineering Services · National industry | 14.12× | 2,410 |
| Manufacturing · Sector | 6.35× | 11,970 |
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 4.37× | 370 |
| Management of Companies and Enterprises · Sector | 3.78× | 1,570 |
| Professional, Scientific, and Technical Services · Sector | 3.51× | 5,590 |
| Utilities · Sector | 1.17× | 100 |
| Temporary Help Services · National industry | 0.72× | 280 |
Related occupations
Part of the Advanced Manufacturing , Arts, Entertainment, & Design and Energy & Natural Resources career clusters.
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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 Materials Engineers — 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.
- Bachelor's degree · typical entry level
- Job zone 4 — Job Zone Four: Considerable Preparation Needed · preparation tier
- Engineering · field of study
Zoom out
On the global GenAI exposure gradient this work sits around the 56th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Materials Engineers show 69th-percentile AI task overlap — and about 1,500 annual U.S. openings
- Materials Engineers rank in the 69th percentile (High 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 1,500 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 about average (+5.7%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $108,310, across about 22,770 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Materials Engineers show 69th-percentile AI task overlap — and about 1,500 annual U.S. openings • Materials Engineers rank in the 69th percentile (High 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 1,500 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 about average (+5.7%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $108,310, across about 22,770 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Materials Engineers". https://singulariki.com/roles/role-17-2131-00 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.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
- BLS Employment Projections 2024–2034 U.S. Bureau of Labor Statistics
- Microsoft “Working with AI” working-with-ai Microsoft Research
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
- ILO / Gmyrek et al. GenAI exposure gradient 2025 International Labour Organization
- IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022 Institute for Structural Research (IBS)
- Frey & Osborne (2013) frey-osborne-automation academic
- Dingel & Neiman (2020) dingel-neiman-workathome academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Plain
Singulariki. "Materials Engineers." 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; 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-17-2131-00
APA
Singulariki. (2026). Materials Engineers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-17-2131-00
BibTeX
@misc{singulariki-role-17-2131-00,
title = {Materials Engineers},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; 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-17-2131-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.