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Tier-1 brand, mid-level ML role, 3+ years, and metro context create high applicant competition.
Core ML engineering skills are broadly transferable, though financial-services familiarity is preferred.
Mandatory 3+ years, ML/LLM expertise, Python and deployment skills create high filtering strictness.
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Design, develop, and deliver components of agentic AI and machine learning products to support international private banking advisors and clients.
Write secure, high-quality production code and maintain algorithms aligned with firm-wide Responsible AI standards including model evaluation and guardrail testing.
Participate in agile processes including code reviews and technical design discussions under direction of senior engineers and team lead.
3+ years of applied AI/ML engineering experience with formal training or certification.
Proficiency in Python and understanding of modern software engineering practices including testing, version control, and code review.
Practical exposure to machine learning and/or Large Language Models (e.g., prompt engineering, RAG, agentic frameworks).
BSc in Computer Science, Data Science, Engineering, or related quantitative field.
Experience working within agile teams and familiarity with software development lifecycle in AI/ML product contexts.
Candidate with hands-on usage of AI coding tools (e.g., Claude Code, GitHub Copilot) integrated into development workflows.
Background or interest in financial services technology and cloud-native deployment concepts (CI/CD, containerization) is preferred but not mandatory.