Overview
In this role you will design, develop, and deploy ML/AI solutions for payments and banking operations, including generative AI, on cloud infrastructure. You work with cross-functional teams to ensure reliable, secure, and observable production systems while translating model outputs into practical decisions. You’ll contribute across the full project lifecycle and drive innovation in payments and banking operations. This role offers growth, hands-on impact, and the chance to shape the future of payments.
Responsibilities
- Deliver ML/AI solutions for payments and banking operations from discovery to production rollout
- Build LLM-powered workflows and evaluate quality, safety, and reliability
- Contribute to deployment workflows including containerization, CI/CD, automated testing, versioning, monitoring, and rollback
- Develop scalable and secure ML/LLM services integrated with strategic platforms
- Collaborate with product, operations, risk and control, and technology teams to clarify requirements
- Build reusable components like feature pipelines, evaluation harnesses, and orchestration patterns
- Participate in code and design reviews; contribute to best practices and documentation
- Communicate model outputs to both technical and non-technical stakeholders; maintain clear documentation
- Maintain documentation such as model cards, runbooks, experiment notes, and operational procedures
Key requirements
- Relevant industry experience in applied ML, data science, ML engineering, or related roles
- Bachelor’s or Master’s degree in a quantitative field
- Strong understanding of ML fundamentals and applied data analysis skills
- Experience designing evaluations and measuring impact in real-world settings
- Experience deploying and operating ML models or ML-enabled services in production
- Strong Python software engineering skills (modular code, testing, debugging)
- Working knowledge of ML engineering/MLOps concepts (training vs. serving, orchestration, governance)
- Ability to align evaluation and guardrails to business goals and identify unintended outcomes
- Experience operating in regulated or control-conscious environments with model risk, privacy, security, and audit-ready documentation
- Strong stakeholder management and teamwork skills for cross-functional outcomes
- Stakeholder management
- Team collaboration
- Communication
- Python programming
- ML/LLM deployment and MLOps
- NLP and generative AI / LLMs
Applied AI ML - Payments Machine Learning (Associate) in London employer: JP Morgan Chase
Morgan is an exceptional employer, offering a dynamic work culture that prioritises diversity and inclusion while fostering employee growth through comprehensive coaching and development opportunities. As a global leader in financial services, we empower our teams to drive impactful product management and AI enablement, ensuring that every employee can contribute meaningfully to our clients' success in a collaborative environment located at the heart of the financial sector.
