Senior Applied AI/ML Engineer, Finance

JPMorganChase; Greater London; Sur place; GBP 70 000 - 90 000; Plein temps

Résumé du poste

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.

Responsabilités

• 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.

Connaissances

Statistics

Machine Learning theory

Natural Language Processing

PyTorch

Docker

Cloud computing (Azure, AWS, GCP)

Formation

Master's or PhD in a quantitative discipline

Outils

pandas

Kubernetes

Description du poste

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.