AI/ML Research Engineer

About the role

This position is based in Switzerland and sits at the intersection of applied research and production‑grade AI engineering. You will design, develop and deploy advanced agentic AI systems and LLM‑powered applications that turn enterprise data into actionable insights and autonomous workflows.

Key responsibilities

• Design, build and scale agentic AI systems and LLM‑based applications with a focus on performance and reliability.
• Develop and fine‑tune AI/ML models in Python, including prompt engineering and integration with modern LLM frameworks.
• Create AI‑assistant and agent‑based solutions that automate complex decision‑making processes.
• Work with large‑scale enterprise data platforms such as SAP HANA, DB2 and SQL Server, using advanced SQL for data processing.
• Evaluate, select and benchmark AI models from providers like OpenAI, Meta, etc., based on use‑case requirements.
• Collaborate with cross‑functional teams to design architecture, integrate models and deploy solutions in cloud environments.

Required profile

• Bachelor’s degree in Computer Science, Data Science, Systems Engineering or equivalent practical experience.
• Strong hands‑on experience with Python and prompt engineering for large language models.
• Proven track record building agentic AI or AI‑assistant applications.
• Solid understanding of NLP and deploying scalable machine‑learning models.
• Extensive SQL expertise and experience with enterprise databases (SAP HANA, DB2, SQL Server).
• Familiarity with cloud AI/ML platforms (Azure AI, AWS ML) and relevant certifications is a plus.

Required skills

• Python
• Prompt Engineering
• Large Language Models (LLMs)
• Natural Language Processing (NLP)
• SAP HANA
• DB2
• SQL Server
• Advanced SQL
• Azure AI
• AWS ML
• Model Context Protocol (MCP)
• Predictive Modeling
• Node.js

What we offer

• Opportunity to work on cutting‑edge AI research and production projects.
• Collaborative, fast‑paced environment with access to state‑of‑the‑art AI frameworks.
• Exposure to enterprise‑scale data systems and cloud infrastructure.