University Graduate – Machine Learning Engineer

During the programme, you will: Identify opportunities for AI and data science to spur data-driven innovations across wealth management. Contribute to the development and validation of AI/ML models that enhance client experience and operational efficiency in a regulated banking environment. Work on real-world use cases such as natural language processing, predictive analytics, and personalization, while ensuring compliance with strict data privacy and security standards. Collaborate with ML engineers, data scientists, and business stakeholders to translate complex requirements into robust, production-ready solutions. Analyze large, high-quality financial datasets to uncover insights and improve model performance, accuracy, and fairness — including visualization and interpretation of model outputs. Participate in the full lifecycle of machine learning solutions, including deployment, monitoring, and ongoing operations (MLOps), ensuring reliability and scalability in live environments. Engage with modern data infrastructure and the Julius Baer (JB) technology stack to build and maintain secure, efficient analytics pipelines. Support model risk management through thorough documentation, assumption testing, and adherence to regulatory expectations on transparency and explainability. Stay ahead of emerging AI/ML trends and apply innovative techniques responsibly within the constraints of banking regulations. Help foster a data-driven culture across the organization by sharing knowledge and promoting best practices in analytics and AI.

Join the COO division and become part of the AI & ML ART (Agile Release Train) of Julius Baer and join one or multiple teams such as the machine learning operations (e.g. deploy/train models on our GPU clusters), embedded AI (automating through AI), Source of Wealth or JAI (our in-house AI chat bot solution) team and work on cutting-edge machine learning and AI topics. By that you will have the opportunity to play a pivotal role in advancing Julius Baer’s business and digital transformation by applying data science and machine learning to real-world banking challenges through hands-on involvement in end-to-end analytics projects, you’ll work across the full lifecycle — from ideation and exploratory analysis to model development, deployment, and ongoing operations. You won’t just build models — you’ll see them deployed into production and actively monitored in live environments and you’ll gain practical experience with modern infrastructure and the Julius Baer (JB) technology stack, enabling scalable and reliable AI solutions. And you will work in a lean, agile environment, you’ll collaborate with experienced colleagues who support continuous learning and growth. You’ll also have regular opportunities to build expertise in cutting-edge areas such as artificial intelligence, scalable data systems, and responsible innovation.

• Master's degree from a university or university of applied sciences with above-average grades in AI, Data Science, Statistics, Mathematics, Physics, Computer Science, or a related quantitative field (graduation max. 12 months ago)

• Initial practical experience in the financial industry and expertise in banking products and financial markets are an asset

• Passion for wealth management and a desire to create value beyond wealth

• A global mindset, excellent interpersonal skills, and a strong appetite for learning

• Fluency in English and German, with additional languages being a plus

• Eligibility to work in the country where you apply for the position