Senior Applied AI/ML Engineer, Finance

JP Morgan Chase; Greater London; On-site; GBP 70,000 - 90,000; Full time

Job summary

JPMorganChase is looking for an Applied AI / ML Senior Associate Machine Learning Engineer to drive innovation in the Commercial & Investment Bank. This role requires a Master's or PhD in a quantitative discipline and strong experience with AI techniques, including Natural Language Processing and machine learning. Candidates should be proficient in PyTorch and familiar with cloud services. The position involves collaborating across teams to build scalable solutions and communicate findings effectively.

Qualifications

• Master's or PhD in a quantitative discipline (Computer Science, Mathematics, Statistics).
• Solid understanding of statistics, optimization, and machine learning theory.
• Extensive experience with PyTorch and data-science Python libraries.
• Experience containerizing applications for deployment (Docker).
• Ability to communicate technical information effectively.

Responsibilities

• Build robust Data Science capabilities across multiple business use cases.
• Collaborate with the software engineering team for Machine Learning integration.
• Research and analyze datasets using statistical and machine learning techniques.
• Communicate AI capabilities to technical and non-technical audiences.
• Document techniques and processes for industry compliance.

Skills

Statistics

Machine Learning theory

Natural Language Processing

PyTorch

Docker

Cloud computing (Azure, AWS, GCP)

Education

Master's or PhD in a quantitative discipline

Tools

pandas

Kubernetes

Job description

JPMorganChase is looking for an Applied AI / ML Senior Associate Machine Learning Engineer to drive innovation in the Commercial & Investment Bank. This role requires a Master's or PhD in a quantitative discipline and strong experience with AI techniques, including Natural Language Processing and machine learning. Candidates should be proficient in PyTorch and familiar with cloud services. The position involves collaborating across teams to build scalable solutions and communicate findings effectively.