Principal MLOps Engineer

Principal AI/MLOps Engineer - Munich, Hybrid

AI Futures, are working with an exciting Global Manufacturing Giant, operating at scale across multiple regions and product lines.

The business is undergoing a significant digital and AI-driven transformation, leveraging advanced machine learning and large language models to optimize operations, improve quality, and unlock new efficiencies across manufacturing, supply chain, and engineering domains.

We are on the search for a Principal MLOps Engineer to help lead this initiative.

Role Responsibilities:

• Implement and automate end-to-end ML and LLM development workflows, covering data preparation, training or fine-tuning, evaluation, deployment, and lifecycle management
• Design, implement, and operationalize LLMOps workflows, including prompt management, Retrieval-Augmented Generation (RAG) pipelines, fine-tuning, and evaluation of LLM-based systems
• Design and operate cloud-native AI infrastructure on AWS and/or Azure, using Infrastructure as Code to ensure scalability.
• Act as a technical leader and enabler for ML teams, translating workflow requirements into platform capabilities and driving adoption of MLOps and LLMOps best practices.

Key Skills & Qualifications:

• Master's degree in Computer Science or equivalent practical experience
• 7+ years of hands-on experience implementing production-level machine learning and AI solutions
• Strong hands-on experience with MLOps, including CI/CD pipelines, model lifecycle management, and production monitoring
• Practical experience operating or integrating LLM-based systems, including prompt engineering, RAG, and fine-tuning workflows
• Experience with MLOps / LLMOps tooling such as SageMaker, Databricks, Hugging Face, LangChain, or LlamaIndex is highly desirable
• Solid cloud engineering background on AWS and/or Azure, with experience designing scalable and secure systems
• Hands-on Infrastructure as Code experience (Terraform, CloudFormation, Bicep/ARM), including CI/CD integration