Continuous Improvement Engineer (Customer Sites)

You have run improvement projects on a live plant. You know that the analysis is the easy part. Getting operators to trust the project, getting honest data out of a running line, and making the improvement survive after you leave, that is the actual work.

We built Oppr because most improvement projects die at that last step. The gain is real for a quarter. Then the person who knew why leaves, the SOP was never updated, and the line drifts back.

About Oppr

Oppr is an AI enabled continuous improvement platform for manufacturing. It connects operator insight with machine data on one timeline. Operators capture what they notice in seconds, by voice, photo or a quick field check, in any language, without forms or a desktop. Findings become verified actions, and verified actions become updated standard work that stays alive.

Founded in 2023 by a former plant manager, backed by leading European venture investors. No new hardware required.

The job is the improvement cycle, run at a customer

You are not implementing software. You are running an improvement project inside a customer's plant, and Oppr is what you run it with.

1. Find the problem that is worth solving. You walk the line and talk to operators, shift leaders and engineers. You separate the stated problem from the real one.
2. Build the hypothesis. You use our internal analysis tooling on the customer's machine data and operator observations to work out what is likely causing it.
3. Design the project. You scope a 10 week Proof of Value that will prove or disprove that hypothesis. Defined measurement, defined pass or fail, agreed with the plant before you start.
4. Get the operators in. You design what they need to capture, you explain why it matters to them, and you stay on the floor until it becomes routine. Nothing else in this list works if this step fails.
5. Gather and analyse. Real data from a running line, not a clean dataset. You work out what it is telling you.
6. Propose the improvement. In production terms and in euros. Downtime, scrap, changeover, first pass yield.
7. Lock it in. This is the part most projects skip. You turn the finding into updated standard work, a check, a trigger or an SOP inside the platform, so the improvement holds after you leave and the lesson is available to the next shift and the next plant.
8. Repeat, faster. Then the same cycle across the rest of the site, using the playbook you wrote doing it the first time.

What this really demands

The hard skill is decomposition. A customer arrives with a frustration, an idea or a KPI that will not move. You have to break that into parts, decide which part is measurable, choose what data would prove it, design the smallest intervention that tests it, and then structure the whole thing so it repeats without you.

That is systems thinking applied to a live process. If you have run DMAIC, built a control plan, written standard work or closed out a Kaizen properly, you already think this way. Here you do it inside a platform, at speed, at a different customer every few months.

Where you work

Most of the work is on site at customers across the Netherlands, Germany and Western Europe. When you are not on a plant floor you work from The Hague or from home.

Operators can tell within five minutes whether you speak their language, and nothing works if they decide you do not. This is a job you do with the customer, not to them.

What we are looking for

• Real shop floor credibility. Process engineer, plant engineer, mechanical engineer, improvement engineer, production engineer, maintenance engineer. The title matters less than the floor time. This is the one thing we cannot teach.
• You have owned an improvement project end to end. Problem definition, plan, operator involvement, data, analysis, improvement, and standardisation. Not a piece of one.
• Structured problem solving. RCA, DMAIC, Lean, Six Sigma, TPM, 8D, whichever school you come from.
• You can say what your improvements were worth, and how you knew.
• You have got operators to change how they work and make it stick. You know the technical part was the easy half.
• Comfortable with data. You can take a messy machine dataset and a set of operator observations and form a defensible hypothesis.
• Comfortable around industrial data systems. MES, SCADA, historians, OPC UA, PLC tags, IoT platforms. You do not need to build them. You need to get data out of them and know what it means.
• Confident enough with software to configure a platform, read a data flow and find the problem yourself.
• Able to run several customer projects at once with your own planning and risk view.
• You hold your own with an operator, a maintenance lead and a plant director on the same day.
• BSc or MSc in mechanical, process, chemical, industrial or automation engineering, or equivalent time served.
• Fluent English. Dutch strongly preferred, German a plus.
• Happy to travel to customer sites regularly.

This is not a software engineering role. You will not write production code and you will not sit behind a desk, but you are heavily involved in improving the tool, getting customer feedback on potential new features, consistently testing the tool and providing feedback. You develop the tool through usage and customer feedback, which you pass on to the development team.

What we offer

• Market conform salary
• Participation in our employee incentive plan
• A ground floor seat with a clear path into Implementation and Support Lead. We intend to fill that seat from within.
• A direct line to the CEO and to the roadmap. What you see in the field ships.
• A new office at Titaan in The Hague and a small international team

We are well funded and growing fast. The work is real, the pace is high, and the shape of the job will change as we scale. We want people who find that energising rather than unsettling.

How to apply

See oppr.ai/careers for the full description, or send a short note and your CV to floris@oppr.ai.

Tell us about one improvement you made on a plant floor. What the symptom was, how you found the cause, how you got the operators involved, and what you did to make sure it held after you moved on.