Industrial Data & Solutions Engineer (gn) @ Stealth AI Venture, Berlin

atlantic.vc - Berlin, Germany - original posting ->
Status
Open
Remote policy
Not stated
Employment type
Not stated
Salary
Not stated
Categories
Portfolio Company
Tech
pythondata
Source
arbeitnow
First observed
2026-09-25 22:05 UTC
Last seen
2026-09-25 22:05 UTC
Source claims posted
2026-09-25 20:30 UTC
Consecutive misses
0 of 3

What the posting says

This is an Atlantic portfolio company.

What we're building

Factories run on machines that generate huge amounts of data, and almost none of it gets used. We're changing that. We build AI software that helps production engineers and operators turn machine data into answers: why a line is slowing down, what's causing scrap, and what to fix next. We're early and in stealth. Our two founders both held C-level roles at leading German robotics ventures. They have spent years bringing advanced technology onto real shop floors, and now they're hiring the founding core team.

Your role & responsibility

You're the person who makes our product work in the real world. You go into a plant, figure out what's actually broken, connect the data, and stay until operators use the product every day without being asked. You'll work with everyone from the machine operator to the plant manager, and with IT and OT. You own each customer from the first conversation through rollout and expansion. Berlin or home-based in Germany, with regular time in Berlin with the team. You'll spend about 20% of your time at customer sites.

What you'll do

Own deployments end to end: use-case definition, data onboarding, validation, rollout, training, and adoption

Turn messy production problems into clear data, analytics, and solution requirements

Onboard and validate machine, process, quality, and maintenance data from industrial systems

Spot data problems that only make sense if you understand the machine behind them

Build and validate KPIs, features, anomaly signals, calibration methods, and analytical workflows in Python and SQL, using statistics and time-series analysis

Run the project with the customer and our commercial lead: plans, workshops, validation sessions, and success criteria

Find the next machine, line, data source, or use case, and expand with it

Bring what you learn in the field back to the product, so each deployment makes the platform better

Help write the playbook for how we deliver, as the customer engineering team grows

You might be a fit if you

Have worked hands-on with industrial machines and production processes, in manufacturing, automation, maintenance, quality, industrial engineering, or industrial data

Know your way around PLCs, SCADA, MES, historians, production databases, quality systems, or OPC UA

Use Python and SQL to answer questions, not just to write code

Have worked with time-series data, KPIs, anomaly detection, or root-cause analysis

Communicate as well on the shop floor as in the plant manager's office

Like solving hard problems in automation and process engineering

Take ownership, work independently, and are comfortable when things are ambiguous

Are happy to travel to customer sites and have a driver's license

Speak fluent German and English

A degree is optional. A Meister, Techniker, vocational training, or real-world experience counts just as much. We care about what you can do.

We're open to experienced people who can lead deployments on their own, and to exceptional earlier-career people with strong industrial experience who learn fast.

This is not a desk job. It's hands-on and customer-facing, and you'll spend a lot of your time where the machines are.

Why now

You'll be one of the first people in the company. You'll work directly with the founders and shape how we deliver to customers from day one. What you build here becomes the way we work. We'll tell you more about the company, the founders, and our backers in the first conversation.

Find Jobs in Germany on Arbeitnow

Quality

Completeness: 45%

Not enough history yet to judge honesty signals.

Timeline

  1. *
    #1006948 2026-09-25 22:05 UTC
    Published