This listing doesn't post a salary. Most similar roles pay
$173,837–$254,750.
Based on 240 similar postings.
Employer
About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1117 open roles
on FindRole.
Listed pay typically runs
$186,160–$215,000
across 7 roles with salary data.
As an Applied AI ML for Payments - Vice President in Wholesale Payments Operations, you will build and deliver enterprise AI/ML solutions to improve operational efficiency and decisioning. You will partner with senior stakeholders to frame problems, define success metrics, and manage roadmaps while mentoring engineers and establishing high engineering standards. Your daily work involves designing and deploying production-grade services on Amazon Web Services using Python to solve complex challenges in document processing, workflow automation, and data mining. You will implement advanced techniques including natural language processing, optical character recognition, and LLM workflows involving retrieval-augmented generation and fine-tuning. Additionally, you will manage MLOps practices, model governance, and responsible AI standards while building scalable data pipelines to support model training and inference for global client payments across multiple currencies and geographies.
Partner with senior stakeholders to define success metrics and align AI/ML roadmaps with business priorities.
Lead the architecture, design, and end-to-end delivery of enterprise AI/ML solutions for wholesale payments.
Write production-quality code and establish engineering standards across the team.
Deploy and operate scalable AI/ML services on AWS infrastructure.
Implement advanced techniques including NLP, OCR, document analysis, and LLM workflows like RAG and fine-tuning.
Design and implement secure data pipelines to support model training and inference.
Establish MLOps practices, model governance, monitoring, and responsible AI protocols.
Mentor engineers and conduct code and design reviews to improve quality and delivery speed.
What we're looking for
Master’s degree in Mathematics, Computer Science, Engineering, or a related quantitative field.
6 years of professional AI/ML experience delivering production systems.
4 years of advanced Python development in production environments using AI-assisted coding tools.
4 years of hands-on experience designing and deploying production machine learning systems on AWS.
Experience building LLM-based applications, including retrieval-augmented generation and fine-tuning workflows.
Experience with NLP, computer vision, OCR, or document AI solutions in production.
Experience implementing MLOps practices using tools like MLflow, Kubeflow, Airflow, feature stores, or model registries.
Experience in wholesale payments, transaction banking, or financial services (preferred); experience with Kubernetes and infrastructure-as-code (preferred).
Machine Learning
Deep Learning
Generative AI
LLMs
NLP
Python
Java
C++
Transformers
Hugging Face
TensorFlow
PyTorch
NumPy
Scikit-Learn
Pandas
AWS
SageMaker
Prompt Engineering
Big Data
LLM
NLP
Machine Learning
Python
Spark
Scala
Java
Data Structures
Algorithms
Search
Big Data
Classification
Regression
Recommender Systems
Databases
System Development