Requirements

Expected technologies

Docker

Kubernetes

Optional technologies

Python

Node.js

Java

TensorFlow

PyTorch

Hugging Face

LangChain

AWS

Google Cloud Platform

Microsoft Azure

Our requirements

• At least 5 years of experience in AI/ML engineering within large-scale, international environments.
• Proven hands-on experience in building and deploying AI solutions, particularly LLMs, chatbots, AI agents, and RAG systems
• Advanced understanding of NLP techniques, machine learning algorithms, and deep learning architectures
• Proficiency in programming languages such as Python and/or Node.js, Java
• Experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, Hugging Face, LangChain).
• Familiarity with MLOps tools (such as MLflow, Kubeflow, Airflow) and best practices in CI/CD for machine learning pipelines.
• Strong knowledge of cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
• Experience with model fine-tuning, prompt engineering, and RLHF.
• Solid knowledge of relational and NoSQL databases and experience with large-scale data processing.
• Fluent German (C1) and ability to work effectively in a distributed, international team.
• Flexible - EMEA Time zone, ideally Germany
• Practical experience working in Agile/Scrum methodology.
• Certification as a PMLE (Professional Machine Learning Engineer) or equivalent qualification is required.

Your responsibilities

• Designing, developing and implementing AI/ML models in areas such as LLMs, chatbots, AI agents, and RAG.
• Integrating AI models with enterprise applications and system infrastructure.
• Analyzing large-scale datasets to train, fine-tune, and improve model performance.
• Collaborating with engineering, data science, and UX teams to deliver high-quality solutions.
• Monitoring the performance of AI systems and optimizing models in production.
• Actively participating in Agile processes, including sprints, planning sessions, and technical discussions.