Job Description

Job Description
We are looking for an AI and Machine Learning Engineer to develop the intelligence that powers ArcGEN. The selected person will be responsible for the design, construction and operation of LLM pipelines, agent architectures and evaluation systems, evolving from notebook prototypes to fully production systems with measurable quality metrics.
Responsibilities:
Design and operate LLM pipelines, including embeddings, vector databases and retrieval systems (RAG).
Develop agent architectures, including tool calling, MCP, subagent orchestration, and complex AI flows.
Build and maintain LLM model evaluation frameworks: metrics, benchmarks, A/B testing and quality gates.
Systematically design and optimize prompts to improve performance and consistency.
Develop machine learning models applied to marketing (attribution, segmentation, forecasting and anomaly detection).
Transform experiments on notebooks into scalable and maintainable productive systems.
Collaborate with full-stack engineers on the integration of AI solutions within the platform.
Requirements:
Practical experience with modern LLM workflows in production: RAG, embeddings and vector databases (Pinecone, Weaviate, pgvector).
Knowledge of Python and libraries such as pandas, NumPy, scikit-learn, PyTorch or TensorFlow.
Experience in systematic evaluation of models using metrics, benchmarks and testing frameworks.
High level of German (C2) and English (C1).
Product-oriented mindset: ability to build systems in production, not just experiments.
Experience with fine-tuning, LoRA or distillation (valuable).
Experience with MLOps tools such as MLflow, Weights & Biases or DVC (valuable).
Experience with agent frameworks such as LangGraph, Mastra or Vercel AI SDK (valuable).
Knowledge of MCP and tool calling architectures (valuable).
Experience in marketing analytics or performance marketing models (valuable).
Contributions in open source, Kaggle or publications in ML/AI (valuable).

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