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 →Postal Service Mail Sorters, Processors, and Processing Machine Operators
Occupation · SOC 43-5053.00
Prepare incoming and outgoing mail for distribution for the United States Postal Service (USPS). Examine, sort, and route mail. Load, operate, and occasionally adjust and repair mail processing, sorting, and canceling machinery. Keep records of shipments, pouches, and sacks, and perform other duties related to mail handling within the postal service. Includes postal service mail sorters and processors employed by USPS contractors.
Also called: Automation Clerk · Distribution Clerk · Mail Handler · Mail Processor · Computer Forwarding System Markup Clerk (CFS Markup Clerk) · Flat Sorting Machine Clerk (FSM Clerk) · Mail Handler Equipment Operator · Mail Processing Clerk · Parcel Post Distribution Machine Operator (PDPMO) · Small Package and Bundle Sorter Clerk (SPBS Clerk) · Assorter · Dead Mail Checker
Job family: Office and Administrative Support Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-43-5053-00/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.
- Declining employment outlook (-8.4% by 2034)
- 7,800 openings/yr
- Low AI exposure
- Median pay $56,530/yr
- Work is mostly on-site (not teleworkable)
- 2013 flagged this for computerization (64th); today's AI task-overlap is comparatively low (9th)
9th-percentile task overlap — yet about 7,800 openings a year (-8.4% 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.) Low | 11th | -1.2 | |
| LLM task exposure, γ (OpenAI / Eloundou) Low | 14th | 0.1 | |
| AI assistant applicability (Microsoft) Low | 14th | 0.1 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.1), and including AI-powered software (γ 0.1). 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 0.8 · 64th percentile among occupations · Moderate
Job outlook
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | Declining · -8.4% by 2034 |
| Projected annual openings | 7,800 |
| Employment 2024 → 2034 | 106,400 → 97,500 |
“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.
Postal Service Mail Sorters, Processors, and Processing Machine Operators sits at the 78th percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure eased from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
41% mean task exposure (2025)
78th percentile of 427 placed occupations
−7 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Mail Carriers and Sorting Clerks · 4412 | 41% | Gradient 2 |
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 17 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Direct items according to established routing schemes, using computer-controlled keyboards or voice-recognition equipment. Supplemental · importance 4.5
- Check items to ensure that addresses are legible and correct, that sufficient postage has been paid or the appropriate documentation is attached, and that items are in a suitable condition for processing. Supplemental · importance 4.5
- Clear jams in sorting equipment. Core · importance 4.4
- Bundle, label, and route sorted mail to designated areas, depending on destinations and according to established procedures and deadlines. Supplemental · importance 4.4
- Operate various types of equipment, such as computer scanning equipment, addressographs, mimeographs, optical character readers, and bar-code sorters. Core · importance 4.3
- Move containers of mail, using equipment, such as forklifts and automated "trains". Supplemental · importance 4.3
- Open and label mail containers. Supplemental · importance 4.3
- Load and unload mail trucks, sometimes lifting containers of mail onto equipment that transports items to sorting stations. Supplemental · importance 4.2
- Distribute incoming mail into the correct boxes or pigeonholes. Supplemental · importance 4.1
- Sort odd-sized mail by hand, sort mail that other workers have been unable to sort, and segregate items requiring special handling. Core · importance 4.1
- Rewrap soiled or broken parcels. Supplemental · importance 4.1
- Train new workers. Supplemental · importance 4.0
- Search directories to find correct addresses for redirected mail. Supplemental · importance 4.0
- Cancel letter or parcel post stamps by hand. Supplemental · importance 3.8
- Accept and check containers of mail from large volume mailers, couriers, and contractors. Supplemental
- Dump sacks of mail onto conveyors for culling and sorting. Supplemental
- Weigh articles to determine required postage. Supplemental
Work activities
- Route mail to correct destinations.
- Package objects for shipping.
- Train personnel.
- Distribute incoming mail.
- Operate computers or computerized equipment.
- Obtain personal or financial information about customers or applicants.
- Maintain office equipment in proper operating condition.
- Verify shipping documentation.
- Attach identification information to products, items or containers.
- Operate vehicles or material-moving equipment.
- Sort mail.
- Load materials or equipment.
- Unload materials or equipment.
- Prepare outgoing mail.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Abilities
| Near Vision | 3.8 | |
| Manual Dexterity | 3.4 | |
| Written Comprehension | 3.1 | |
| Information Ordering | 3.1 | |
| Category Flexibility | 3.1 | |
| Perceptual Speed | 3.1 | |
| Multilimb Coordination | 3.1 | |
| Static Strength | 3.1 | |
| Oral Comprehension | 3.0 | |
| Oral Expression | 3.0 | |
| Problem Sensitivity | 3.0 | |
| Deductive Reasoning | 3.0 | |
| Finger Dexterity | 3.0 | |
| Trunk Strength | 3.0 | |
| Speech Recognition | 3.0 | |
| Speech Clarity | 3.0 | |
| Inductive Reasoning | 2.9 | |
| Selective Attention | 2.9 | |
| Arm-Hand Steadiness | 2.9 | |
| Control Precision | 2.9 | |
| Extent Flexibility | 2.9 | |
| Far Vision | 2.6 | |
| Written Expression | 2.5 | |
| Reaction Time | 2.5 |
Essential skills
| Monitoring | 3.1 | |
| Reading Comprehension | 3.0 | |
| Speaking | 3.0 | |
| Critical Thinking | 3.0 | |
| Active Listening | 2.9 |
Knowledge
| English Language | 3.0 | |
| Production and Processing | 2.5 | |
| Customer and Personal Service | 2.4 |
Transferable skills
| Coordination | 3.0 | |
| Operations Monitoring | 2.9 | |
| Judgment and Decision Making | 2.9 | |
| Time Management | 2.9 | |
| Social Perceptiveness | 2.8 | |
| Operation and Control | 2.8 | |
| Service Orientation | 2.5 | |
| Complex Problem Solving | 2.5 |
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
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 2 — Job Zone 1-2: Very Little to Some Preparation Needed
- Education
- Usually requires a high school diploma or GED, though some occupations may not.
- Typical entry-level education
- No formal educational credential · BLS, the typical path — not a requirement
- Related experience
- Some occupations may need little or no previous experience; others require several months to a year of experience. For example, landscaping and groundskeeping workers might require very little training or previous experience, while agricultural equipment operators can benefit from on-the job training.
- Preparation level
- SVP (Below 6.0) — total schooling plus on-the-job experience.
Education of current workers
Share of people in this occupation at each level of education.
| High School Diploma | 81.4% | |
| Less than a High School Diploma | 12.5% | |
| Some College Courses | 6.1% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Conventional | 5.9 | |
| Realistic | 4.6 | |
| Social | 1.8 | |
| Enterprising | 1.7 | |
| Investigative | 1.5 |
Interest areas
| Physical/Manual Labor | 3.6 | |
| Mechanics/Electronics | 3.0 | |
| Transportation/Machine Operation | 2.3 | |
| Office Work | 2.2 | |
| Accounting | 1.6 | |
| Information Technology | 1.6 | |
| Engineering | 1.6 | |
| Management/Administration | 1.3 |
Work styles
| Attention to Detail | 2.4 | |
| Dependability | 2.3 | |
| Integrity | 1.4 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $42,600 |
| 25th percentile | $47,380 |
| Median (50th) | $56,530 |
| 75th percentile | $72,970 |
| 90th percentile | $74,050 |
| People employed | 111,930 |
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 |
|---|---|---|
| Transportation and Warehousing · Sector | 111,920 | $56,530 |
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 |
|---|---|---|
| Transportation and Warehousing · Sector | 20.86× | 111,920 |
Related occupations
Part of the Public Service & Safety career cluster.
- Mail Clerks and Mail Machine Operators, Except Postal Service · 43-9051.00 Compare →
- Shipping, Receiving, and Inventory Clerks · 43-5071.00 Compare →
- Postal Service Clerks · 43-5051.00 Compare →
- Stockers and Order Fillers · 53-7065.00 Compare →
- Office Machine Operators, Except Computer · 43-9071.00 Compare →
- Weighers, Measurers, Checkers, and Samplers, Recordkeeping · 43-5111.00 Compare →
- Data Entry Keyers · 43-9021.00 Compare →
- Laborers and Freight, Stock, and Material Movers, Hand · 53-7062.00 Compare →
- Recycling and Reclamation Workers · 53-7062.04 Compare →
- File Clerks · 43-4071.00 Compare →
- Packers and Packagers, Hand · 53-7064.00 Compare →
- Postmasters and Mail Superintendents · 11-9131.00 Compare →
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 Postal Service Mail Sorters, Processors, and Processing Machine Operators — 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.
- No formal educational credential · typical entry level
- Job zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed · preparation tier
Zoom out
On the global GenAI exposure gradient this work sits around the 78th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Postal Service Mail Sorters, Processors, and Processing Machine Operators show 9th-percentile AI task overlap — and about 7,800 annual U.S. openings
- Postal Service Mail Sorters, Processors, and Processing Machine Operators rank in the 9th percentile (Low 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 7,800 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 declining (-8.4%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $56,530, across about 111,930 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Postal Service Mail Sorters, Processors, and Processing Machine Operators show 9th-percentile AI task overlap — and about 7,800 annual U.S. openings • Postal Service Mail Sorters, Processors, and Processing Machine Operators rank in the 9th percentile (Low 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 7,800 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 declining (-8.4%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $56,530, across about 111,930 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Postal Service Mail Sorters, Processors, and Processing Machine Operators". https://singulariki.com/roles/role-43-5053-00 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. "Postal Service Mail Sorters, Processors, and Processing Machine Operators." 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-43-5053-00
APA
Singulariki. (2026). Postal Service Mail Sorters, Processors, and Processing Machine Operators. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-43-5053-00
BibTeX
@misc{singulariki-role-43-5053-00,
title = {Postal Service Mail Sorters, Processors, and Processing Machine Operators},
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-43-5053-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.