Full-Stack Engineer – ML Platform, Applied AI – Vice President

Salary: £62,000 - 102,000 per year

Requirements:

• Degree in a quantitative discipline such as Computer Science, Mathematics, or Statistics
• Strong knowledge of and hands-on experience with Python
• Broad understanding of the software stack, including front end, back end, cloud architecture, messaging and queue systems, databases, security, and network configurations
• Experience with AWS and Kubernetes
• Ability to develop and deploy business-critical, data-intensive applications
• Strong understanding of computer science fundamentals and development best practices
• Ability to understand business objectives and align machine learning problem definitions accordingly
• Experience in machine learning engineering roles
• Familiarity with higher-level interfaces such as Pydantic AI and Langraph
• Proficiency in TypeScript
• Experience mentoring others or leading teams
• Experience designing reusable libraries and services
• Interest in bridging scientific theory with enterprise-grade systems
• Passion for innovation and continuous learning

Responsibilities:

• Design and deliver enterprise-grade machine learning systems
• Implement distributed, multi-threaded, and scalable applications
• Build, test, and deploy secure automated pipelines for cloud systems, desktop applications, and machine learning solutions
• Apply software engineering and computer science best practices
• Develop and deploy business-critical, data-intensive applications
• Leverage foundational libraries and services for reuse across teams
• Use MLOps tools for versioning, reproducibility, and observability
• Collaborate with cloud and site reliability engineering teams to build robust production architectures

Technologies:

• AI
• AWS
• Cloud
• Kubernetes
• Machine Learning
• MLOps
• Network
• Python
• Security
• TypeScript
• Agentic AI
• Support
• Fullstack

More:

We are hiring a Full Stack Engineer - ML Platform, Applied AI, for our Doc AI team within Commercial and Investment Banking. You will work at the intersection of software engineering and applied research to build production architectures and next-generation AI products, with flexibility to pursue an individual contributor path or optional people leadership opportunities. Our DocAI team builds, deploys, and maintains document-processing models and platforms, including a next-generation AI platform and desktop application for automating document-centric workflows at enterprise scale in a highly regulated environment. We offer global collaboration, mentorship, career growth, and opportunities to contribute to impactful projects. J.P. Morgan is a global financial services leader, and our Commercial & Investment Bank serves corporations, governments, and institutions in more than 100 countries. We value diverse talent and are an equal opportunity employer.

last updated 40 week of 2026