Cleaners of Vehicles and Equipment vs Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders
Side-by-side · O*NET · BLS · AI-exposure research · Anthropic Economic Index
A factual, source-backed comparison of Cleaners of Vehicles and Equipment and Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders on the dimensions both occupations carry. Every figure is a position within an independent published dataset — not a verdict on which job is better, safer, or more “future-proof.”
At a glance
| Dimension | Cleaners of Vehicles and Equipment | Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders |
|---|---|---|
| Median pay | $35,270 | $49,500 |
| Employment | 373,960 | 54,200 |
| Employment outlook (2024–34) · BLS projection | About average (+3.9%) | Declining (-4.3%) |
| Annual openings · BLS projection | 56,200 | 5,400 |
| Typical education · O*NET | Usually requires a high school diploma or GED, though some occupations may not. | Usually requires a high school diploma or GED, though some occupations may not. |
| AI exposure · published exposure studies | Low · 7th pct | Low · 31st pct |
| Global GenAI gradient · ILO ISCO-08 · via crosswalk | 3rd pct · 10% of tasks | 41st pct · 23% of tasks |
| Observed AI use · Anthropic Economic Index | — | — |
| Mostly remote-capable · Dingel–Neiman | No | No |
Pay and employment are BLS OEWS estimates; outlook and openings are BLS 2024–2034 projections; AI exposure and observed-use figures come from separate research and reflect exposure and usage, not predictions that either job will disappear. Compare like with like.
Skills
Shared: Near Vision, English Language, Manual Dexterity, Extent Flexibility, Multilimb Coordination, Operation and Control, Quality Control Analysis, Problem Sensitivity, Finger Dexterity, Control Precision, Trunk Strength, Operations Monitoring, Oral Comprehension, Deductive Reasoning, Arm-Hand Steadiness, Production and Processing, Monitoring, Time Management, Oral Expression, Information Ordering, Speech Recognition, Mechanical, Active Listening, Inductive Reasoning, Category Flexibility, Far Vision.
Specific to Cleaners of Vehicles and Equipment
- Customer and Personal Service
- Transportation
- Stamina
- Administration and Management
- Public Safety and Security
- Gross Body Coordination
- Speaking
- Speech Clarity
Specific to Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders
- Perceptual Speed
- Reaction Time
- Critical Thinking
- Flexibility of Closure
- Selective Attention
- Static Strength
- Reading Comprehension
- Judgment and Decision Making
Knowledge, skills & abilities O*NET rates as important for each occupation. “Shared” are common to both; the columns list what is distinctive to each (top by the order O*NET surfaces).
Tools & technology
Specific to Cleaners of Vehicles and Equipment
Specific to Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders
Full profiles
This page is a summary. See the complete source-backed profile for Cleaners of Vehicles and Equipment or Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders — tasks, the full skill graph, tools, work context, preparation, wages by percentile, industries, AI exposure and the AI work map.
More comparisons
Related occupations you can place side by side on the same sourced scale.
- Cleaners of Vehicles and Equipment vs Laundry and Dry-Cleaning Workers
- Cleaners of Vehicles and Equipment vs Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders
- Cleaners of Vehicles and Equipment vs Janitors and Cleaners, Except Maids and Housekeeping Cleaners
- Cleaners of Vehicles and Equipment vs Septic Tank Servicers and Sewer Pipe Cleaners
- Cleaners of Vehicles and Equipment vs Maintenance Workers, Machinery
- Cleaners of Vehicles and Equipment vs Coating, Painting, and Spraying Machine Setters, Operators, and Tenders
- Cleaners of Vehicles and Equipment vs Machine Feeders and Offbearers
- Cleaners of Vehicles and Equipment vs Home Appliance Repairers
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
Singulariki. "Cleaners of Vehicles and Equipment vs Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders." 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/compare/cleaners-of-vehicles-and-equipment-vs-separating-filtering-clarifying-precipitating-and-still-machine-setters-operators-and-tenders
Singulariki. (2026). Cleaners of Vehicles and Equipment vs Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/compare/cleaners-of-vehicles-and-equipment-vs-separating-filtering-clarifying-precipitating-and-still-machine-setters-operators-and-tenders
@misc{singulariki-cleaners-of-vehicles-and-equipment-vs-separating-filtering-clarifying-precipitating-and-still-machine-setters-operators-and-tenders,
title = {Cleaners of Vehicles and Equipment vs Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders},
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/compare/cleaners-of-vehicles-and-equipment-vs-separating-filtering-clarifying-precipitating-and-still-machine-setters-operators-and-tenders}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.