AI Platform Engineer (f/m/d)

Job description

About Munich Electrification Munich Electrification is an innovative company founded with the aim of accelerating the transition to electric and connected mobility. We develop innovative electronic control units for electric vehicles and stationary storage systems for our global customers. Our international team is composed of highly motivated and exceptional engineers. As a small and specialized team we are well-aware of the importance of each individual colleague and support and promote each employee according to their abilities and needs. Our office with adjacent prototype and testing lab is located in the heart of Munich at the Heimeranplatz. This is what we stand for: - Technological Leadership : We challenge norms, innovate quickly, and anticipate future needs. We take smart risks and learn from outcomes to stay ahead. - Sustainability : We actively drive change for a sustainable future, aware of our impact and inspiring others to build a better world. - Team Culture : We believe work should be enjoyable, fostering a spirit of inspiration, celebration, and teamwork across the globe. - Entrepreneurial Spirit : We embrace change, think big, and push limits with passion. Your role As an AI Platform Engineer, you will be a key architect of the software and systems that empower our AI-driven initiatives. More than just managing infrastructure, you will be actively building the cohesive, end-to-end platform that enables our teams to develop, deploy, and scale applications rapidly. You will engineer robust backend services, create internal tools, and design the automated workflows that form the foundation of our AI capabilities. If you are a software engineer passionate about building scalable platforms and bringing AI models to life through high-quality code, this is the perfect opportunity for you. As part of your role, you would maintain and develop: Develop Core Platform Services: Design, build, and operate the backend services and APIs that serve our AI models and manage the ML lifecycle. Develop the Data Ingestion Platform: Design, build, and maintain the services and automated workflows responsible for populating our vector and graph databases, ensuring our AI applications have access to timely and accurate data Build Full-Stack Tooling: Create user-facing tools and internal dashboards that allow developers, data scientists and managers to interact wi…