About the Role
AI Futures has been exclusively retained to hire a hands-on Founding ML Engineer for a well-funded, early-stage AI startup based in Berlin. This is a high-impact opportunity to shape the machine learning capabilities of an enterprise AI platform from the ground up. The role sits at the intersection of applied AI, machine learning engineering and enterprise data, with a focus on turning complex, unstructured and inconsistent business information into reliable, structured data that powers intelligent workflows.
Responsibilities
•Own the design, development and deployment of core machine learning systems, taking models from experimentation through to production
•Build AI-powered extraction and transformation pipelines that turn complex enterprise documents and data sources into structured, reliable outputs
•Develop solutions for working with tabular data, unstructured information and inconsistent enterprise datasets
•Design and implement LLM-based systems, information extraction workflows and intelligent automation capabilities
•Work with real-world corporate workflows, integrating AI into existing business processes and enterprise systems
•Build robust evaluation frameworks to measure model accuracy, reliability and performance across varied data types and use cases
•Work across the stack, from data preparation and model experimentation to deployment, monitoring and optimisation
•Establish the technical foundations for the company's ML capabilities, making pragmatic architectural decisions in a fast-moving startup environment
•Use modern AI engineering tools and development practices to accelerate iteration and deliver production-ready solutions
Requirements
•Strong experience in machine learning engineering, applied AI or a closely related technical discipline, ideally with experience taking AI systems into production
•Excellent Python skills and a solid understanding of data processing, model development and production engineering
•Experience building AI-powered extraction pipelines, document intelligence systems or structured data processing solutions
•Familiarity with tabular data, complex schemas and transforming inconsistent data into clean, structured outputs
•Exposure to corporate workflows, enterprise environments or business-critical operational processes
•Experience with LLMs, prompt engineering, retrieval-augmented generation (RAG), structured outputs or related applied AI techniques
•Strong understanding of model evaluation, testing and the challenges of deploying reliable AI systems in production
•A practical, experimental mindset, with the ability to move quickly from prototype to robust implementation
•Comfortable operating in an early-stage environment, taking ownership of technical decisions and helping shape the company's ML architecture
•Languages: German (English a bonus)
Nice to have: Finance experience preferred, particularly exposure to financial data, financial documents or finance-related workflows
Conditions
Up to €120k package + VSOP
