ml engineer for fintech

JPMorganChase provides financial services, including strategic advice and products to corporations, governments, wealthy individuals, and institutional investors. Chase UK is its digital bank, focused on mobile banking.

• Deliver AI/ML applications and services that improve customer experiences and increase operational efficiency
• Work across the AI/ML delivery lifecycle, from stakeholder requirements and solution design through prototyping, evaluation, deployment support, monitoring, and iteration
• Develop Python-based AI/ML solutions on AWS/GCP, contributing production-ready code as part of a delivery team
• Build and evaluate AI/LLM solutions, including prompt/RAG patterns and agentic workflows, alongside classical ML where appropriate
• Apply ML techniques to forecasting, segmentation/CLV, causal inference, and other business problems
• Analyze large, heterogeneous datasets using SQL to generate insights, validate assumptions, and track impact
• Collaborate with stakeholders and cross-functional delivery teams
• Produce clear documentation, reports, and presentations for technical and non-technical audiences
• Support governance activities, including model/data-use documentation and technical input to risk, privacy, and controls assessments

• Familiarity with AI/LLM development patterns and frameworks, including prompt engineering, RAG, LangChain/LangGraph and/or Google ADK
• Strong Python and SQL skills, with the ability to write clean, production-ready code
• Strong AI/ML fundamentals, including statistics, probability, linear algebra, and model evaluation
• Experience with scikit-learn and either PyTorch or TensorFlow
• Practical DevOps mindset, including testing, CI/CD, reproducibility, code quality, and operational awareness
• Excellent written and verbal communication; able to explain technical trade-offs clearly
• Collaborative, curious, and comfortable working with ambiguity
• Будет плюсом: experience delivering AI/ML solutions in a regulated financial organisation, AWS and/or GCP cloud experience (AWS preferred), experience with S3, Lambda, Glue, Athena, Iceberg, Vertex AI, BigQuery, GCS, Cloud Run, or Pub/Sub, experience with AI/ML observability and evaluation tools such as MLflow, LangSmith, LLM-as-a-Judge, guardrails, or production monitoring, exposure to fine-tuning or continuous learning techniques such as PEFT/LoRA

• Условий в вакансии нет