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 →Ship Engineers
Occupation · SOC 53-5031.00
Supervise and coordinate activities of crew engaged in operating and maintaining engines, boilers, deck machinery, and electrical, sanitary, and refrigeration equipment aboard ship.
Also called: Engineer · Ferry Engineer · Port Engineer · Tug Boat Engineer · Barge Engineer · Harbor Engineer · Ship Engineer · Towboat Engineer · Vessel Engineer · Deck Engineer · Engineering Watch Officer · Equipment Maintenance Marine Engineer
Job family: Transportation and Material Moving Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-53-5031-00/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 (+1.6% by 2034)
- 1,100 openings/yr
- Low AI exposure
- Median pay $101,320/yr
- Work is mostly on-site (not teleworkable)
20th-percentile task overlap — yet about 1,100 openings a year (+1.6% 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.) Moderate | 34th | -0.5 | |
| LLM task exposure, γ (OpenAI / Eloundou) Low | 27th | 0.2 | |
| AI assistant applicability (Microsoft) Low | 4th | 0.0 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.2), and including AI-powered software (γ 0.2). 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 · 22nd 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 · +1.6% by 2034 |
| Projected annual openings | 1,100 |
| Employment 2024 → 2034 | 8,800 → 9,000 |
“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.
Ship Engineers sits at the 42nd 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.
23% mean task exposure (2025)
42nd percentile of 427 placed occupations
−6 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Ships' Engineers · 3151 | 23% | 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 17 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Monitor engine, machinery, or equipment indicators when vessels are underway, and report abnormalities to appropriate shipboard staff. Core · importance 4.8
- Monitor the availability, use, or condition of lifesaving equipment or pollution preventatives to ensure that international regulations are followed. Core · importance 4.8
- Monitor and test operations of engines or other equipment so that malfunctions and their causes can be identified. Core · importance 4.7
- Start engines to propel ships, and regulate engines and power transmissions to control speeds of ships, according to directions from captains or bridge computers. Core · importance 4.7
- Perform or participate in emergency drills, as required. Core · importance 4.6
- Perform general marine vessel maintenance or repair work, such as repairing leaks, finishing interiors, refueling, or maintaining decks. Core · importance 4.5
- Maintain or repair engines, electric motors, pumps, winches, or other mechanical or electrical equipment, or assist other crew members with maintenance or repair duties. Core · importance 4.5
- Maintain complete records of engineering department activities, including machine operations. Core · importance 4.5
- Operate or maintain off-loading liquid pumps or valves. Core · importance 4.4
- Maintain electrical power, heating, ventilation, refrigeration, water, or sewerage systems. Core · importance 4.2
- Install engine controls, propeller shafts, or propellers. Core · importance 4.2
- Clean engine parts and keep engine rooms clean. Core · importance 4.2
- Record orders for changes in ship speed or direction, and note gauge readings or test data, such as revolutions per minute or voltage output, in engineering logs or bellbooks. Core · importance 4.0
- Order and receive engine room stores, such as oil or spare parts, maintain inventories, and record usage of supplies. Core · importance 4.0
- Act as a liaison between a ship's captain and shore personnel to ensure that schedules and budgets are maintained and that the ship is operated safely and efficiently. Supplemental · importance 4.0
- Supervise marine engine technicians engaged in the maintenance or repair of mechanical or electrical marine vessels, and inspect their work to ensure that it is performed properly. Core · importance 3.8
- Fabricate engine replacement parts, such as valves, stay rods, or bolts, using metalworking machinery. Supplemental · importance 3.7
Emerging tasks
Newer responsibilities O*NET has flagged as growing for this occupation.
- Use drone technology for ship inspections, maintenance, or other tasks.
Work activities
- Monitor availability of equipment or supplies.
- Monitor engine operation or functioning.
- Report vehicle or equipment malfunctions.
- Maintain watercraft engines or machinery.
- Record operational details of travel.
- Direct emergency management activities.
- Record operational or production data.
- Operate ships or other watercraft.
- Control pumps or pumping equipment.
- Clean facilities or work areas.
- Clean machinery or equipment.
- Direct maintenance or repair activities.
- Acquire supplies or equipment.
- Communicate with others to coordinate vehicle movement.
- Install parts, assemblies, or attachments in transportation or material handling equipment.
- Fabricate products or components using machine tools.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Mechanical | 4.5 | |
| English Language | 3.5 | |
| Engineering and Technology | 3.5 | |
| Public Safety and Security | 3.5 | |
| Transportation | 3.3 | |
| Mathematics | 3.3 | |
| Computers and Electronics | 3.2 |
Abilities
| Oral Comprehension | 4.0 | |
| Oral Expression | 4.0 | |
| Problem Sensitivity | 4.0 | |
| Deductive Reasoning | 4.0 | |
| Written Comprehension | 3.6 | |
| Control Precision | 3.6 | |
| Near Vision | 3.6 | |
| Speech Clarity | 3.5 | |
| Speech Recognition | 3.4 | |
| Inductive Reasoning | 3.3 | |
| Information Ordering | 3.3 | |
| Written Expression | 3.1 | |
| Category Flexibility | 3.1 | |
| Flexibility of Closure | 3.1 | |
| Visualization | 3.1 | |
| Selective Attention | 3.1 | |
| Arm-Hand Steadiness | 3.1 | |
| Manual Dexterity | 3.1 |
Essential skills
| Critical Thinking | 3.9 | |
| Active Listening | 3.6 | |
| Monitoring | 3.6 | |
| Speaking | 3.5 | |
| Active Learning | 3.3 | |
| Reading Comprehension | 3.1 |
Transferable skills
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 3 — Job Zone Three: Medium Preparation Needed
- Education
- Most occupations in this zone require training in vocational schools, related on-the-job experience, or an associate's degree.
- Typical entry-level education
- Postsecondary nondegree award · BLS, the typical path — not a requirement
- Related experience
- Previous work-related skill, knowledge, or experience is required for these occupations. For example, an electrician must have completed three or four years of apprenticeship or several years of vocational training, and often must have passed a licensing exam, in order to perform the job.
- Preparation level
- SVP (6.0 to < 7.0) — total schooling plus on-the-job experience.
What to study: Transportation and Materials Moving . 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.
| High School Diploma | 48.0% | |
| Post-Secondary Certificate | 23.9% | |
| Post-Baccalaureate Certificate | 10.8% | |
| Bachelor's Degree | 8.2% | |
| Some College Courses | 6.2% | |
| Less than a High School Diploma | 3.1% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Work styles
| Dependability | 8.0 | |
| Attention to Detail | 7.0 | |
| Integrity | 6.0 | |
| Cautiousness | 5.0 | |
| Self-Control | 4.0 | |
| Stress Tolerance | 3.0 |
Interest areas
| Mechanics/Electronics | 6.5 | |
| Engineering | 6.3 | |
| Transportation/Machine Operation | 6.3 | |
| Management/Administration | 3.5 | |
| Physical/Manual Labor | 3.3 | |
| Information Technology | 2.2 |
Career interests (Holland / RIASEC)
| Realistic | 6.4 | |
| Conventional | 4.9 | |
| Enterprising | 3.7 | |
| Investigative | 3.5 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $56,620 |
| 25th percentile | $71,720 |
| Median (50th) | $101,320 |
| 75th percentile | $130,380 |
| 90th percentile | $162,370 |
| People employed | 8,580 |
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 | 5,680 | $104,560 |
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 250 | $130,380 |
| Construction · Sector | 190 | $88,510 |
| Manufacturing · Sector | 120 | $80,520 |
| Educational Services · Sector | 70 | $98,720 |
| Arts, Entertainment, and Recreation · Sector | 40 | $74,140 |
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 | 13.81× | 5,680 |
| Mining, Quarrying, and Oil and Gas Extraction · Sector | 7.83× | 250 |
| Construction · Sector | 0.42× | 190 |
| Manufacturing · Sector | 0.17× | 120 |
Related occupations
Part of the Supply Chain & Transportation career cluster.
- Stationary Engineers and Boiler Operators · 51-8021.00 Compare →
- Marine Engineers and Naval Architects · 17-2121.00 Compare →
- Maintenance and Repair Workers, General · 49-9071.00 Compare →
- Hydroelectric Plant Technicians · 51-8013.04 Compare →
- Sailors and Marine Oilers · 53-5011.00 Compare →
- Motorboat Mechanics and Service Technicians · 49-3051.00 Compare →
- Bus and Truck Mechanics and Diesel Engine Specialists · 49-3031.00 Compare →
- Aircraft Mechanics and Service Technicians · 49-3011.00 Compare →
- Locomotive Engineers · 53-4011.00 Compare →
- Avionics Technicians · 49-2091.00 Compare →
- Aircraft Structure, Surfaces, Rigging, and Systems Assemblers · 51-2011.00 Compare →
- Operating Engineers and Other Construction Equipment Operators · 47-2073.00 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 Ship 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.
- Postsecondary nondegree award · typical entry level
- Job zone 3 — Job Zone Three: Medium Preparation Needed · preparation tier
- Transportation and Materials Moving · field of study
Zoom out
On the global GenAI exposure gradient this work sits around the 42nd percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Ship Engineers show 20th-percentile AI task overlap — and about 1,100 annual U.S. openings
- Ship Engineers rank in the 20th 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 1,100 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 (+1.6%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $101,320, across about 8,580 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Ship Engineers show 20th-percentile AI task overlap — and about 1,100 annual U.S. openings • Ship Engineers rank in the 20th 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 1,100 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 (+1.6%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $101,320, across about 8,580 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Ship Engineers". https://singulariki.com/roles/role-53-5031-00 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. "Ship 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-53-5031-00
APA
Singulariki. (2026). Ship Engineers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-53-5031-00
BibTeX
@misc{singulariki-role-53-5031-00,
title = {Ship 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-53-5031-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.