Applied AI ML Engineer - Associate

We know that people want great value combined with an excellent experience from a bank they can trust, so we launched our digital bank, Chase UK, to revolutionise mobile banking with seamless journeys that our customers love. We're already trusted by millions in the US and we're quickly catching up in the UK – but how we do things here is a little different. We're building the bank of the future from scratch, channelling our start-up mentality every step of the way – meaning you'll have the opportunity to make a real impact.
As an Applied AI/ML Engineer - Associate at JPMorgan Chase within the International Consumer Bank, you will be a part of a flat-structure organization. Your responsibilities are to contribute to the delivery of end-to-end cutting-edge solutions in the form of cloud-native microservices architecture applications leveraging the latest technologies and the best industry practices. You are expected to be involved in the delivery and implementation of those solutions.
Our Applied AI/ML team is at the heart of this venture, focused on getting smart ideas into the hands of our customers. We're looking for people who have a curious mindset, thrive in collaborative squads, and are passionate about new technology. By their nature, our people are also solution-oriented, commercially savvy and have a head for fintech. We work in tribes and squads that focus on specific products and projects – and depending on your strengths and interests, you'll have the opportunity to move between them.
Job responsibilities
Deliver AI/ML applications and services that improve customer experiences and increase operational efficiency.
Work across the AI/ML delivery lifecycle: stakeholder requirements, solution design, 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.
Analyse large, heterogeneous datasets using SQL to generate insights, validate assumptions, and track impact.
Collaborate with stakeholders (e.g., product owners, operations management, marketing/acquisition) and cross-functional delivery teams.
Produce clear documentation, reports, and presentations for technical and non-technical audiences.
Support required governance activities, including model/data-use documentation and technical input to risk, privacy, and controls assessments.
Required qualifications, capabilities and skills
Familiarity with AI/LLM development patterns and frameworks, including prompt engineering, RAG, LangChain/LangGraph and/or Google ADK.
Strong Python and SQL; able 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: 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.
Preferred qualifications, capabilities and skills
Experience delivering AI/ML solutions in a regulated financial organisation.
Cloud experience on AWS and/or GCP, with AWS preferred.
Experience with tools such as 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.
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