Ready to shape the future of smart manufacturing?At FactoryPal, we’re redefining how factories perform—connecting shopfloors through cutting-edge software to improve transparency, efficiency, and decision-making. Our B2B SaaS solution empowers manufacturers to optimize performance and reach new levels of operational excellence.Backed by Valmet and Körber, FactoryPal combines the energy of a start-up with the reach and credibility of two global leaders in industrial technology. Headquartered in Berlin, we’re scaling a solution that’s already transforming manufacturing operations across tissue and other sectors.Your Role & Key ResponsibilitiesDevelop and deploy sophisticated machine learning models to solve key business challenges.Engineer and maintain robust, scalable ML pipelines for both real-time and batch data processing, ensuring high availability and performance.Manage the end-to-end ML lifecycle, from experimentation and versioning to monitoring and deployment, using modern MLOps principles.Apply best practices in software engineering, including CI/CD and Infrastructure-as-Code (IaC), to streamline model delivery and ensure reliability.Conduct in-depth statistical analysis and data exploration to extract actionable insights that guide product decisions and model development.Translate complex results into clear insights for technical and non-technical stakeholders.Your Experience & Key SkillsBachelor's degree in Software Engineering, Data Science, STEM, or a related technical/quantitative field3+ years of experience as a Machine Learning Engineer, Data Scientist/Engineer, Software Engineer or similar role4+ years of experience in Python and its core data science libraries, including pandas, NumPy, scikit-learn, and PyTorch3+ years of experience building, managing, and scaling data pipelines3+ years experience with cloud technologies (preferably AWS)2+ years experience with SQLHands-on experience integrating AI coding assistants and agentic AI workflows into the development process to boost productivity and code qualityNice to HaveMaster’s degree in Software Engineering, Data Science, STEM, or a related technical/quantitative fieldExperience with orchestration tools, preferably AirflowExperience with real-time data stream processing and model servingExperience with AI Engineering and LLMsExperience with ML lifecycle management tools like MLflow for experiment tracking and model registryExperience in manufacturing or IIoTWhat You GetA central role in a fast-scaling corporate start-up backed by Valmet and KörberA chance to shape the manufacturing industry with new innovationsExposure to cutting-edge technologies like AI/ML, Industrial IoT, and Cloud SaaS High impact: direct influence on company growth and customer success Access to key decision makers across FactoryPal and our investors Flexible, hybrid work setupCompetitive salary and 30 days vacation A dedicated training budget and training days Subsidized Wellhub membership giving you access to thousands of gyms, fitness studios, wellness services, and mental health resources worldwide An international, diverse, and high-performance team with a shared missionAre you interested?If you are interested in becoming part of the team, you can apply by March 6th, 2026, by filling in our online application form, attaching you CV in English.Please kindly note that we do not accept applications or CVs via email.If you have questions about the role, please contact the hiring manager Zach Eberhart, Head of Data Science. Email: zach.eberhart@valmet.comDie personenbezogenen Daten, die Sie uns im Rahmen dieses Bewerbungsprozesses innerhalb unserer Bewerberplattform (Workday) zur Verfügung stellen, werden von dem Verantwortlichen, Valmet GmbH Marienburgstr. 35 64297 Darmstadt, zum Zwecke des Auswahlverfahrens für die angegebene Stellenanzeige verarbeitet. Rechtsgrundlage ist hier Art. 6 Abs. 1 lit. b DSGVO (Durchführung vorvertraglicher Maßnahmen). Die Daten werden nach Abschluss des Verfahrens, spätestens nach 6 Monaten, gelöscht. Sie haben das Recht auf Auskunft, Löschung, Sperrung, Datenübertragbarkeit und zur Beschwerde bei der zuständigen Aufsichtsbehörde.