The Industrial FDE

Day one in the plant

Day one is a night shift, not a notebook. The line's quality data lives in an Excel the third-shift supervisor keeps on a USB stick. A vision sensor has been miscalibrated since March, and everyone works around it. The Industrial FDE's first week is spent on the floor: talking to the production chief, tracing where the data actually comes from, and finding the one process step where a model would pay for itself.

Weeks later there is a system running on the line — not a slide deck. That is the whole job: the distance between a model that works in a demo and a system a plant runs at 3 a.m. without calling anyone. The FDE closes that distance in person, on site, inside the constraints of a production schedule that does not stop for experiments.

The day-to-day mixes three kinds of work that rarely live in one person: process engineering (understanding what the line actually does, and why the workarounds exist), data work (pipelines from PLCs, historians and hand-kept spreadsheets), and deployment (getting a model into production hardware, with fallbacks the operators trust).

Why the labs can't find them

The AI labs employ thousands of engineers who can build models. Almost none of them have stood on a production floor, negotiated with a maintenance crew, or shipped a change during a running shift. That half of the profile is built over years inside plants — and it is the half the market is short of.

The imbalance is measurable: AI leadership vacancies are growing four times faster than qualified candidates [SOURCE], and frontier labs are signing joint ventures directly with manufacturers to get deployment capacity [SOURCE]. When a company needs someone who understands both powder-coat inspection and convolutional networks, the search space is small enough that generalist job boards return noise. That specificity is exactly what the searches in this pool are drawn to.

Compensation, with sources

Every role in the Industrial AI Jobs pool publishes its base salary range — the numbers below summarize what those searches pay in the US market.

Ranges vary by sector: regulated industries (pharma packaging, food safety) and multi-site rollouts sit at the top of each band; single-line pilots at the bottom. Roles that prefer the Certified Industrial FDE credential say so on the listing, and companies can filter the pool by it.

How you become one

Most Industrial FDEs start where you might be now: an automation, process or quality engineer who knows a plant inside out, or a lean or quality consultant with a portfolio of factories. The plant half of the profile is already built. The applied-AI half — data pipelines, model deployment, MLOps under industrial constraints — can be learned, and the roles in this market expect proof of real deployment, not certificates alone.

What the searches in this pool consistently ask for:

• Years on the floor — credibility with operators and maintenance is screened for, not assumed.
• One real deployment — a system you put into production, however small, beats any portfolio of notebooks.
• Process specificity — companies describe searches at the level of "vision QA on powder-coated plastics", and profiles that name their processes match first.

If that is your profile — or your next twelve months — one interview puts you in front of every matching search, current and future. Free for candidates, always.

Frequently asked questions