GenAI/ML Engineer for Portfolio Analysis System (f/m/d) - 1-Year Fixed-Term Contract bei Lgt

LGT is the world’s largest family-owned and managed Private Banking and Asset Management Group. For more than 100 years it has been fully owned and managed by the Princely House of Liechtenstein, which is also one of our biggest clients.
With around 800 employees, LGT Bank Switzerland has established itself as a renowned Swiss private bank and is an excellent address for both wealthy private clients and employees - this was also confirmed last year by the independent institute "Great Place To Work", which awarded LGT Bank Switzerland the title of one of the best employers in Switzerland.

Job Description

• You have deep knowledge and professional experience in Machine Learning, Large Language Models, Retrieval-Augmented Generation (RAG) systems, Python development, and financial data analysis for research and development of an AI-driven portfolio analysis system.
• You will be working on building a production-grade system including RAG, semantic search with vector databases, integration with commercial news providers, market data APIs, and LLM deployment using open-source models.
• You are a self-starter with strong ownership, able to drive complex ML projects from conception to production, and maintaining high standards for accuracy, documentation, and professional delivery.

Requirements

• Deep understanding of Large Language Models (LLMs) and practical experience deploying open-source models in production environments
• Expert-level skills in Python with deep knowledge of ML frameworks
• Experienced with data management pipelines (relational and unstructured)
• Professional or academic experience building validation frameworks to ensure AI accuracy and prevent hallucinations, including fact-checking systems, citation mechanisms, and source attribution
• Experience with financial time series data analysis and market data processing
• Fluent in English (both written and spoken), with ability to explain complex technical concepts to non-technical stakeholders including portfolio managers and executives
• Growth mindset with eagerness to learn new technologies and stay current with rapidly evolving LLM and RAG techniques

Qualifications

• MSc or PhD degree in Computer Science, Machine Learning, AI, Mathematics, Physics, or related quantitative field
• At least one year of professional or academic experience in ML engineering, specifically working with LLMs
• Demonstrable track record through GitHub repositories, publications, or production systems deployed

Contact Information

For further information please do not hesitate to contact us.

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