Experteer Overview

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As an ML Engineer at Julius Baer, you will design, build, and maintain scalable AI solutions within a DevOps context. You’ll work across the full lifecycle—from concept to deployment—collaborating with cross-functional teams to deliver digital solutions. You will create multi-agent systems, enable AI with function/tool-calling capabilities, and ground AI responses in enterprise data using RAG approaches. This role offers the chance to shape AI-driven wealth management solutions at scale.

Compensaciones / Ventajas
• Develop, deploy, and optimize AI/ML solutions for complex business challenges
• Create multi-agent systems and enable tool-calling for AI models
• Design and implement RAG systems grounded in enterprise data
• Evaluate and integrate AI models (e.g., LLMs) for performance and reliability
• Optimize agentic workflows for production use cases
• Test and refine system prompts and few-shot examples for safe AI outputs




• Assess model performance with appropriate metrics and iterate
• Collaborate with platform teams, data engineers, and stakeholders to integrate ML solutions
• Participate in code reviews, testing, and debugging to ensure quality and reliability of ML solutions

Responsabilidades
• Strong problem-solving and analytical abilities
• Excellent communication and collaboration skills for cross-functional work
• Ability to manage workload, prioritize, and meet deadlines
• Continuous learning mindset with up-to-date ML/AI knowledge
• Attention to detail and quality-focused coding
• Bachelor’s or Master’s in relevant field
• Proven experience xghoner with Large Language Models (LLMs)
• Good understanding of AI agents, orchestration frameworks, and reasoning patterns
• Experience with data preprocessing, feature engineering, and model evaluation
• Knowledge of statistics, linear algebra, and optimization

📌 Machine Learning Engineer 100% (Madrid)
🏢 Julius Bär
📍 Madrid