Senior Applied AI Engineer - MLOps

About the Role

CyberTide GmbH is seeking an experienced Applied AI Engineer specializing in MLOps to join our team. This role involves deploying, fine-tuning, and optimizing large language models (LLMs) for cloud and on-premises environments, with a strong focus on efficiency.

What You Will Do

• Deploy and manage AI and LLM models across various platforms including AWS, Azure, GCP, and on-premises infrastructure, with a preference for Azure.
• Enhance model performance using advanced techniques such as parameter-efficient fine-tuning (e.g., LoRA, QLoRA).
• Implement AI model inference frameworks like vLLM to improve speed and efficiency.
• Apply advanced prompt engineering techniques and principles to improve model outputs.
• Ensure AI models are designed to enhance user experience and address end-user needs effectively.
• Collaborate with clients to deliver tailored technical solutions, translating customer requirements into effective AI approaches.
• Collaborate closely within a small, agile startup team, where your ideas and expertise will have a direct impact. Exhibit strong communication skills to articulate concepts clearly and contribute meaningfully across diverse functions.

Your Profile

• At least 3 years of experience in machine learning engineering, with a minimum of 1 year working specifically with LLMs, prompt engineering, deployment, and operationalization.
• Ability to work legally in Germany on a full-time basis. Unfortunately, we do not offer visa sponsorship.
• Proven experience deploying and managing AI models in production environments.
• Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
• Familiarity with the Hugging Face ecosystem, including Transformers library and Model Hub. Contributions to the Hugging Face community or experience with Hugging Face Spaces is a plus.
• Experience with containerization technologies such as Docker and Kubernetes.
• Proven experience in deploying and managing solutions across major cloud platforms (AWS, Azure, GCP) as well as on-premises infrastructure.
• Sufficient knowledge of AI model inference techniques and frameworks, including Retrieval-Augmented Generation (RAG) for enhancing contextual understanding and response generation.
• Fluent in English. German or French language skills are preferred, as they align with our target market.
• Ability to continuously learn and adapt cutting-edge techniques to enhance model performance and deployment efficiency.
• Thrive in a fast-paced startup environment where rapid iteration and efficient delivery are essential to success, ensuring consistently high-quality results within tight deadlines.