EXPOSED
The core of this job — installing, calibrating, and troubleshooting robotic cells, PLC-controlled lines, servo drives and sensor arrays — happens with hands on hardware in noisy, non-standard plant environments that robots cannot service themselves. What AI erodes is the desk half: reading schematics, drafting test reports, interpreting fault logs, writing ladder logic and HMI screens, and generating maintenance documentation. There is no license gate here, so the moat is physical access and diagnostic judgment when a machine fails in a way the manual never described.
Dipped in 2020, then grew past where it started.
Median pay $58,350 → $73,900 +1.3% in real terms
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.
BLS projection, 2024–2034
+1.1% 15,000 → 15,100 on the projections basis
Growing, and only partly exposed
The BLS expects +1.1% more of these jobs by 2034, and at 55/100 the work is only partly exposed — some tasks are automatable, the core of the job is not. Nothing here is in tension.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~1,300 openings a year on average, including replacing people who leave.
TesterDrone PilotRemote PilotDrone OperatorRobot OperatorRobotic WelderDrone TechnicianElectro-MechanicRobot ProgrammerRobot TechnicianRework SpecialistRework TechnicianRobotics MechanicSensor TechnicianRobotic TechnicianAssembly TechnicianMechanical DesignerProcess Control TechAutomation TechnicianInstrument SpecialistInstrument TechnicianRobotics TechnologistUnderwater RoboticistCalibration Technician
Holding it up: embodiment . Weakest point: liability shield .
Tasks largely resist digitisation Physically re-shimming a misaligned harmonic drive, running a laser alignment on a gantry, tracing an intermittent encoder fault back to a chafed cable in a wire tray — these are the tasks that keep this at 14 rather than 18, because the parallel half of the job (interpreting PLC fault codes, writing test procedures, building HMI screens, producing calibration reports) is exactly what code generation and log analysis tools now do well.
Hands-on in uncontrolled environments An 18 reflects that the work happens inside the machine envelope — lockout/tagout on a live line, crawling into a robot cell to reteach points, probing a 480V drive cabinet with a scope, and doing it on a plant floor with vibration, coolant mist and no fixed workspace; it stops short of 20 only because a meaningful share of bench calibration and simulation happens in a controlled lab.
No licence, no signature requirement A 3 is right because nothing in this role requires a state licence: employers ask for an associate degree in mechatronics or EET, maybe a vendor cert (Siemens, Allen-Bradley, FANUC) or an NFPA 70E arc-flash qualification, but the PE stamp on the machine design and the OSHA exposure both belong to the engineer and the employer, not the technician who commissioned it.
Meaningful discretion 13 is earned by the calls made with the line down and production shouting: deciding whether a servo fault is mechanical binding or a tuning problem, whether to bypass an interlock to test (and whether that is safe), whether a machine is fit to run another shift — real discretion with cost and injury consequences, but the final release-to-production and any design change go up to an engineer, which keeps it out of the 14+ band.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (14/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (3/20) is whether the law requires a licensed human to sign. Trust premium (7/20) is whether buyers specifically pay for a person. Judgment and accountability (13/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 23 of this occupation's 55 points (42%).
Embodiment (18/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
Avionics Technicians SAFE
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 70/100 — SAFE.
ANSI/RIA R15.06 and the emerging R15.08 mobile-robot standard becoming a de facto condition of workers' comp coverage, with the risk-assessment document requiring a signature from the technician who performed it.
Task-mix shift as AI absorbs the desk tier: ladder-logic drafting, HMI screen generation, fault-log summarization and O&M documentation are the automatable half. What remains is commissioning a cell that behaves differently than simulated, chasing intermittent faults with no log signature, and mechanical alignment. This raises the score only if headcount is not cut proportionally to the desk work removed — the residual job is denser but there is less of it.
Adoption of functional-safety sign-off requirements that name a qualified person rather than a firm: ISO 13849 / IEC 62061 validation records and OSHA 1910.147 lockout-tagout verification already require a documented competent person, and TÜV/Exida Functional Safety Technician certification is increasingly written into OEM warranty and insurer terms. If a state or an insurer requires a named certified safety technician to personally attest to guard, light-curtain and e-stop validation after any robotic cell change — as some carriers now demand before covering collaborative-robot installs — the attestation becomes non-delegable.
Formalization of the restart decision: if plant safety programs or insurer conditions require the technician to be the named authority who releases a line back to production after a safety-system fault — rather than a supervisor or an automated interlock reset — the consequential call becomes owned rather than advisory.
Already near ceiling at 18. Marginal increase only if the installed base shifts further toward high-mix, retrofit and brownfield integration, where no digital twin exists and physical measurement is unavoidable.
The limit. Embodiment is nearly maxed and cannot carry much more. Trust premium has no realistic route — buyers are plant engineering managers and integrators purchasing uptime, not a human touch, and no credible mechanism makes an industrial customer pay extra for human-performed calibration. The whole upside sits in liability, and it depends on functional-safety attestation attaching to a named individual rather than to an integration firm, which is not the current default in US practice.
| Boston-Cambridge-Newton, MA-NH | 750 | $73,630 +0% |
| Detroit-Warren-Dearborn, MI | 610 | $62,120 -16% |
| San Jose-Sunnyvale-Santa Clara, CA | 540 | $77,030 +4% |
| Los Angeles-Long Beach-Anaheim, CA | 500 | $92,360 +25% |
| Seattle-Tacoma-Bellevue, WA | 360 | $100,090 +35% |
| Dallas-Fort Worth-Arlington, TX | 330 | $52,160 -29% |
| New York-Newark-Jersey City, NY-NJ | 290 | $72,300 -2% |
| San Francisco-Oakland-Fremont, CA | 290 | $109,990 +49% |
| San Francisco-Oakland-Fremont, CA | 290 | $109,990 +49% |
| Toledo, OH | 40 | $109,890 +49% |
| Bridgeport-Stamford-Danbury, CT | 30 | $103,780 +40% |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 55. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.