Machine Learning Engineering & Applied AI ML Lead

JP Morgan Chase; Greater London; On-site; GBP 62,000 - 102,000; Full time

Job summary

JP Morgan Chase is seeking an experienced machine learning engineer to design and deliver enterprise-grade ML systems within a global financial services context. You will collaborate with cloud and SRE teams to build robust production architectures and translate scientific research into scalable ML solutions.

The role requires strong CS fundamentals, extensive AWS and Kubernetes experience, and proficiency with PyTorch and NumPy.

Qualifications

• Experience in machine learning engineering roles.
• Degree in a quantitative discipline (CS, Math, or Stats).
• Proven ability to deploy business-critical, data-intensive apps.
• Extensive AWS and Kubernetes experience.
• Proficiency with PyTorch and NumPy.
• Hands-on in distributed, multi-threaded, scalable apps.

Responsibilities

• Design and deliver enterprise-grade ML systems.
• Collaborate with cloud and SRE teams for robust production architectures.
• Translate scientific research into scalable ML solutions.
• Develop and deploy business-critical data-intensive applications.
• Implement distributed, multi-threaded, scalable apps.
• Build, test, and deploy automated ML pipelines.
• Leverage libraries and services for reuse across teams.
• Apply software engineering and CS best practices.
• Utilize MLOps tools for versioning and observability.
• Align ML problems with business objectives.
• Mentor and support team members; potential for management.

Skills

Machine learning engineering

ML pipelines

Mentoring / leadership

Agentic AI concepts

CS fundamentals

MLOps tooling

Reusable libraries

Business alignment

Education

Degree in Computer Science, Mathematics, or Statistics

Tools

AWS

Kubernetes

PyTorch

NumPy

Job description

Salary: £62,000 - 102,000 per year

Requirements:

• Experience in machine learning engineering roles
• Degree in a quantitative discipline such as Computer Science, Mathematics, or Statistics
• Proven ability to develop and deploy business-critical, data-intensive applications
• Extensive experience with AWS and Kubernetes
• Proficiency with lower-level libraries such as PyTorch and NumPy
• Hands-on experience implementing distributed, multi-threaded, and scalable applications
• Experience with automated building, testing, and deployment pipelines
• Familiarity with higher-level interfaces such as Pydantic AI and LangGraph
• Strong understanding of computer science fundamentals and development best practices
• Broad knowledge of MLOps tooling for versioning, reproducibility, and observability
• Ability to understand business objectives and align ML problem definitions
• Experience mentoring or leading teams
• Knowledge of agentic AI concepts
• Experience designing reusable libraries and services
• Interest in bridging scientific theory and enterprise-grade systems
• Passion for innovation and continuous learning

Responsibilities:

• Design and deliver enterprise-grade machine learning systems
• Collaborate with cloud and SRE teams to build robust production architectures
• Translate scientific research into scalable ML solutions
• Develop and deploy business-critical, data-intensive applications
• Implement distributed, multi-threaded, and scalable applications
• Build, test, and deploy automated pipelines for ML solutions
• Leverage foundational libraries and services for re-use across teams
• Apply best practices in software engineering and computer science
• Utilize MLOps tools for versioning, reproducibility, and observability
• Align ML problem definitions with business objectives
• Mentor and support team members, with optional management responsibilities

Technologies:

• Agentic AI
• AI
• AWS
• Cloud
• Support
• Kubernetes
• Machine Learning
• MLOps
• PyTorch
• numpy
• Security

More:

We are a global leader in financial services and our Commercial & Investment Bank serves corporations, governments, and institutions in more than 100 countries. We are building an AI platform and desktop application to automate document processing workflows at the worlds largest bank, with systems already operating at hundreds of documents per second and scaling rapidly. You will join our Applied Artificial Intelligence and Machine Learning team within Commercial & Investment Banking, working at the intersection of software engineering and scientific research. We offer career growth, mentorship, flexibility for individual contributors with optional management responsibilities, and the opportunity to help shape our team culture while driving impactful change. We are committed to diversity, inclusion, and equal opportunity across our global workforce.

last updated 36 week of 2026