Applied AI/ML Lead, Payments

JPMorgan Chase

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Seattle, WA
Posted: 64 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $216k

$171k most similar roles pay here $260k

This listing doesn't post a salary. Most similar roles pay $185,000–$246,150.

Based on 240 similar postings.

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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.

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At a glance

TL;DR · Applied AI/ML Lead, Payments

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As a Vice President, Applied AI/ML Lead - Payments within the Commercial & Investment Bank, you will lead the end-to-end delivery of document extraction and natural language processing capabilities to improve trust, safety, and operational efficiency in payment systems. You will own the entire lifecycle from problem framing and data strategy to production deployment while setting technical direction for scalable model pipelines involving text extraction, classification, and ranking. The role requires hands-on development of NLP algorithms to extract entities and signals from unstructured documents. You will utilize Python, PyTorch or TensorFlow, SQL, and Spark within cloud environments like AWS. Key responsibilities include establishing model lifecycle practices, defining evaluation metrics, and ensuring audit-ready processes for risk and compliance. Your work focuses on solving complex document understanding challenges in a regulated financial services environment.

Skills

Artificial Intelligence Machine Learning Natural Language Processing Python PyTorch TensorFlow SQL Spark Document Extraction Optical Character Recognition

What you'll do

Own end-to-end delivery of document extraction and natural language processing solutions from initial sizing to production rollout.
Design scalable model pipelines for document ingestion, text extraction, classification, and ranking while balancing accuracy and cost.
Develop NLP algorithms to extract entities, relationships, and signals from unstructured text and documents.
Define evaluation strategies, success metrics, and robust testing protocols for all deployed models.
Establish model lifecycle practices including monitoring, drift detection, and incident response to ensure production reliability.
Partner with risk and compliance stakeholders to ensure audit-ready processes and explainable model behaviors.
Drive technical decisions through design reviews and code reviews to improve quality and delivery velocity.
Translate complex model behaviors into decision-ready business impact for senior stakeholders.

What we're looking for

Formal training or certification in applied artificial intelligence and machine learning concepts.
5+ years of experience in applied artificial intelligence and machine learning.
5+ years of experience building and delivering production-level machine learning or natural language processing solutions.
Proficiency in Python and modern machine learning frameworks like PyTorch or TensorFlow.
Hands-on experience with document extraction, text classification, and information extraction techniques.
Experience designing data-driven solutions using SQL and distributed processing tools such as Spark.
Experience deploying and operating machine learning services in cloud environments like AWS.
Ability to translate ambiguous business problems into structured machine learning plans and communicate technical tradeoffs to stakeholders.