Senior AI Engineer

AI Engineer (all genders) Have you ever held the output of one of your models in your hand? Most ML engineers never will. Their models rank, recommend, classify, forecast. The result lives on a dashboard. Here, the result is a physical object. Made overnight, shaped to the scan of one specific person, shipped to that person. If the model got it wrong, someone feels it. A Hamburg based hardware and software startup that manufactures a consumer product on demand, one unit at a time, each shaped to an individual body scan. No molds, no standard sizes, no warehouse full of guesses. The technology is their own, it is the first of its kind, and it is now moving from proof to scale. The team is engineers, designers and the kind of people who read a manufacturing textbook and ask why. Backed by founders and investors with real conviction. Still small enough that your work reaches the production floor without passing through a committee. This is not a research role with a factory in the background. It is ML inside the factory. The data comes off scanners, machines and sensors that were never designed to make your life easy. You own the whole loop. Raw scan, telemetry and production data go in one end. A monitored model doing useful work in a live system comes out the other. Feature engineering, training, deployment, drift, iteration. And the judgment calls in between: when a model is good enough, when it isn't, and when the right answer is that the problem doesn't need ML at all. What You'll Do Build and maintain ETL pipelines that turn raw scan, telemetry and production data into something a model can learn fromDesign, train and ship models that solve real production and product problems, then keep them runningOwn the lifecycle end to end: acquisition, features, training, deployment, monitoring, iterationIntegrate models into software and production systems. "It works in the notebook" is where the job starts, not where it ends.Run experiments and evaluate them without flinching, including the ones that don't support your hypothesisWork with software, hardware and product colleagues to turn ambiguous problems into ML solutions, or to say clearly when ML is the wrong toolStay current with the field without chasing every paper that trends for a week What You Bring Experience as an ML/AI Engineer with models you have shipped to production and kept alive. Not negotiable.Strong Python and real fluency with NumPy, Pandas and sklearnETL experience with messy, high volume, real world data, not curated benchmark setsHands on deep learning with PyTorch or TensorFlowML fundamentals deep enough to explain why a model fails, rather than retraining with new hyperparameters and hopingSoftware engineering discipline: clean code, version control, tests, and the ability to operate what you build once it's liveCloud experience on AWS or GCPHamburg, on site. Hardware and software get built in the same room here, and so do the arguments that make both better. What Would Make Us Sit Up Computer vision is the obvious one. Scanning, quality control and production inspection are where many of the interesting problems live. Beyond that: NLP applied to internal tools or the customer experience, MLOps you have actually run (Docker, Kubernetes, CI/CD for models, drift detection), time spent with sensor or manufacturing data, and open source contributions in ML. All of it counts. ---------------------------------------- We give companies a face with the right people. At workidentity, we support IT and Finance professionals and leaders who want to take their next step with clarity, strategy, and real long-term perspective. At the same time, I help mid-sized companies fill key positions, whether they are growing, planning succession, or repositioning. For us, these two things belong together: creating opportunities for candidates and strengthening companies with the right personalities. What you gain as a candidate: ✅ Access to roles that are rarely advertised publicly ✅ Fast, transparent communication instead of weeks of silence ✅ Structured matching that prioritizes fit, not chance ✅ Guidance on whether a role truly aligns with your long-term goals ✅ A career partner who takes your values, strengths, and impact seriously At the same time, workidentity represents a work culture that sees diversity as a driver of innovation. As a member of the Diversity Charter, we live a culture with intention and integrity. If you want to find out whether we can identify your next role together or whether a current opportunity is the right match for you: 👉 Secure a non-binding 30-minute call.