Machine Learning Engineer

About the Role

Julius Baer is looking for a machine learning engineer to join an agile ML and AI team. The position focuses on building dependable, scalable AI solutions in a DevOps setting, with involvement from early ideation through to production deployment. You will work closely with different teams to deliver digital products that are robust, useful, and aligned to business needs.

Key Responsibilities

• Build, release, and refine machine learning and AI systems that solve complex business problems.
• Develop multi-agent setups and enable AI models to use tools and functions.
• Architect and implement retrieval-augmented generation solutions that anchor responses in internal enterprise data.
• Evaluate and integrate AI models, including large language models, with a focus on reliability and performance.
• Improve agent-based workflows and prepare AI agents for real production scenarios.
• Test and tune system prompts and few-shot examples so outputs remain accurate, consistent, and safe.
• Measure model performance using suitable metrics, evaluation datasets, and assessment methods, then keep iterating for better results.
• Work with platform, data engineering, data science, and other business teams to embed ML capabilities into existing systems and workflows.
• Take part in code reviews, testing, and debugging to maintain solution quality and stability.

Risk and Compliance Expectations

The role requires conduct aligned with the organization’s standards on honesty, integrity, due care, diligence, fair dealing, conflict-of-interest management, professional competence, continuous learning, risk control, and adherence to all relevant laws and regulations.

Candidate Profile

We are seeking someone who combines strong technical depth with clear communication, teamwork, and a structured approach to delivery. A commitment to continuous learning, attention to detail, and the ability to manage multiple tasks effectively are important for success in this role.

Requirements

• A bachelor’s or master’s degree in Data Science, Computer Science, Mathematics, Statistics, or a similar discipline.
• Solid Python programming ability, along with hands-on experience using machine learning and deep learning frameworks such as TensorFlow or PyTorch.
• Practical experience working with large language models.
• Good understanding of AI agents, agentic workflows, orchestration frameworks, and reasoning patterns for LLM systems.
• Experience in data preprocessing, feature engineering, model selection, and evaluation.
• Knowledge of the mathematical and statistical foundations of machine learning, including probability, linear algebra, and optimization.
• Awareness of software engineering best practices such as version control, testing, and documentation.
• Strong debugging and issue-resolution skills.
• Relevant professional experience in machine learning, data science, or a related area.
• Strong analytical thinking and problem-solving ability.
• Effective communication and collaboration skills for working across functions and seniority levels.
• Ability to organize work, prioritize tasks, manage timelines, and deliver high-quality output.

Additional Information

Julius Baer emphasizes individuality, empowerment, entrepreneurship, and creating value beyond wealth. The company invites applicants through its online application process and also offers the option to create a candidate account for job alerts. A career site is mentioned as a place to explore other opportunities.