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Machine Learning Engineer 100%
Julius Baer sucht einen Machine Learning Engineer für sein Responsible AI-Programm in Zürich, der skalierbare KI-Lösungen und LLM-basierte Agenten-Workflows entwickelt. Die Rolle umfasst die gesamte Lebenszyklusverwaltung von der Konzeption bis zur Implementierung in einer DevOps-Umgebung.
YOUR PROFILE
- Strong problem-solving and analytical skills, with the ability to think critically and creatively about complex challenges
- Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and stakeholders at all levels of the organization
- Ability to manage personal workloads efficiently, to prioritize tasks, manage timelines, and deliver high-quality results on schedule
- Continuous learning mindset, with a passion for staying up-to-date with the latest advancements in machine learning and artificial intelligence
- Attention to detail and commitment to producing high-quality, reliable, and maintainable code
- Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field
- Strong programming skills in Python with experience in machine learning libraries and deep learning frameworks
- Proven experience working with Large Language Models (LLMs)
- Good understanding of AI agents & agentic workflows, LLM orchestration frameworks and related patterns
- Experience with data preprocessing, feature engineering, and model selection and evaluation techniques
- Knowledge of statistical and mathematical concepts relevant to machine learning, such as probability, linear algebra, and optimization
- Understanding software development best practices, including version control, testing, and design and implement new systems or projects
Tasks
- Assist and integrate AI models (e.g. LLMs) ensuring optimal performance and reliability
- Optimize agentic workflows and AI agents for production use cases
- Testing and optimizing systems through tests and ensure accurate, consistent, and safe outputs
- Performance evaluation of continuous model testing and improve them over time
- Collaborate with platform teams, data scientists, and other stakeholders to build AI/ML solutions into existing systems and process
- Participate in code reviews, testing, and debugging to ensure the quality and reliability of machine learning solutions
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