Machine Learning Engineer – m/f/d

This is a fully remote position, open to applicants in Germany.

📋 Description

• Create applications based on Large Language Models (LLM).

• Design conversational systems and semantic search, integrating them into industry-specific applications.

• Establish and sustain Retrieval-Augmented Generation (RAG) systems.

• Manage knowledge bases, including indexing, updates, and the organized storage of both structured and unstructured content.

• Oversee system operations and monitoring.

• Implement MLOps in production, focusing on observability, structured logging, and error analysis.

• Ensure consistent reliability of systems in a production environment, beyond initial functionality.

• Deploy agents into a live production setting.

• Handle the entire process from development through integration and connection to portal systems, ensuring stable delivery.

• Enhance solutions using data-driven insights.

• Utilize monitoring data, testing, and user feedback to iteratively refine solutions.

• Explore innovative approaches.

• Discover new AI use cases, prototype them, and create data pipelines from preprocessing and model development to production.

⛳️ Requirements

• Minimum of 3 years of professional experience as a Machine Learning Engineer, focused on the design, development, implementation, and optimization of scalable ML solutions.

• At least 2 years of experience collaborating in agile development teams.

• Proficiency in German at a C1 level (both spoken and written), validated by a language certificate or as a native speaker.

• A completed degree in Computer Science, Business Informatics, or a related field, verifiable through a certificate or self-declaration.

• Experience with vector search and semantic indexing in vector databases, preferably Milvus.

• Backend development expertise in Python, ideally with FastAPI.

• Familiarity with LLM orchestration using LangChain or LangGraph.

• Experience in operating production-grade AI systems, including monitoring (preferably with Grafana), structured logging, error analysis, and deployment.

• Knowledge of privacy-compliant AI design, especially regarding personal data handling in logging and observability.

• Experience with Generative AI used by multiple users, ideally in a multi-tenant environment.

• Proficiency in Kubernetes, ArgoCD, and Jenkins.

• Familiarity with agile delivery structures, preferably SAFe.

• Experience from projects within the public administration sector.

🏝️ Benefits

• Engage in real production projects.

• Work on AI solutions deployed at customer sites.

• Not just an innovation lab — focus on actual deployments, rather than presentations.

• Remote-first approach within the DACH region.

• Occasional on-site presence; otherwise, work from your most productive location.

• Access to a modern AI stack.

• Involvement with RAG, agents, vector search, and MLOps.

• Utilize a current tech stack without legacy constraints.

• Opportunities for internal upskilling.

• Commitment to investing in your AI skill development.

• MacBook provided, unless the client supplies their own hardware.

• Enjoy a flat hierarchy.

• Founders serve as your direct contacts.

• Be part of a team that values connection, even when working remotely.