VP, Applied AI/ML for Payments Technology

J.P. Morgan

New York (NY)

On-site

USD 180,000 - 260,000

Full time

14 days+

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Benefits offered by this job

Health care coverage
Retirement savings plan
On-site wellness centers
Tuition reimbursement
Mental health support

Job summary

JPMorganChase is seeking a Vice President, Applied AI and Machine Learning Lead in Payments Technology within the Commercial & Investment Bank. This role leads end-to-end document extraction and NLP initiatives, owning problem framing, data strategy, deployment, and measurement while guiding cross-functional teams across product, engineering, data, risk, and compliance.

You will balance hands-on work with setting technical direction, advocating for robust model lifecycle practices, and ensuring

Qualifications

  • 5+ years of applied ML/NLP experience in production.
  • Strong Python skills with PyTorch or TensorFlow.
  • Experience with SQL and distributed processing tools (Spark).
  • Cloud deployment experience on AWS or equivalent.

Responsibilities

  • Own end-to-end delivery of document extraction and NLP solutions, from scoping to production rollout.
  • Design scalable model pipelines for ingestion, extraction, classification, and ranking.
  • Develop NLP algorithms to extract entities, relationships, and signals from text and documents.
  • Define evaluation strategies and success metrics, including offline validation and online measurement.

Skills

Python
NLP
ML modelling
Communication

Education

Formal AI/ML training

Tools

PyTorch
TensorFlow
SQL
Spark

Job description

JPMorganChase is seeking a Vice President, Applied AI and Machine Learning Lead in Payments Technology within the Commercial & Investment Bank. This role leads end-to-end document extraction and NLP initiatives, owning problem framing, data strategy, deployment, and measurement while guiding cross-functional teams across product, engineering, data, risk, and compliance.

You will balance hands-on work with setting technical direction, advocating for robust model lifecycle practices, and ensuring

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