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About the Role

FactoryPal is redefining how factories perform by 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. We are looking for a Senior Machine Learning Engineer who sits at the intersection of data science and data engineering, with experience in building models and engineering pipelines for production.

Responsibilities

Develop 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.

Requirements

Professional working proficiency in English
3+ years of experience as a Machine Learning Engineer, Data Scientist/Engineer, Software Engineer or similar role
4+ years of experience in Python and its core data science libraries, including pandas, NumPy, scikit-learn, and PyTorch
3+ years of experience building, managing, and scaling data pipelines
3+ years experience with cloud technologies (preferably AWS)
2+ years experience with SQL
Hands-on experience integrating AI coding assistants and agentic AI workflows into the development process to boost productivity and code quality

Skills

Python
pandas
NumPy
scikit-learn
PyTorch
AWS
SQL
CI/CD
Infrastructure-as-Code (IaC)
MLOps
AI coding assistants
agentic AI workflows

Location

Berlin

Work Type

Hybrid

Experience Level

Senior

Education Level

Bachelor's degree in Software Engineering, Data Science, STEM, or a related technical/quantitative field
Master’s degree in Software Engineering, Data Science, STEM, or a related technical/quantitative field

Benefits

Competitive salary
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

About the Company

FactoryPal is redefining how factories perform by 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.
FactoryPal, a joint venture by Valmet and Körber – fully consolidated to Valmet, is dedicated to strengthening global production capacities amid a growing shortage of skilled workers.
By optimizing resources, reducing waste, and enhancing operational efficiency, FactoryPal aims to ensure a continuous supply of goods for both current and future generations.
FactoryPal is a multiple time awarded modular software as a service application that empowers shop floor teams to achieve seamless operations and optimized production.
Acting as an AI co-pilot, the application leverages data and AI to transform operational challenges into opportunities, optimizing many aspects of production.
FactoryPal is industry- and machine-agnostic, catering to diverse manufacturing needs in continuous and batch production processes across Europe and the Americas.

Equal Opportunity

To protect our candidates' privacy, we will never ask any personal information such as banking information or social security number during the recruitment process.