Applied AI/ML Lead
Listed on 2026-07-21
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Software Development
Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Location: New York
JOB DESCRIPTION
Are you passionate about harnessing the power of artificial intelligence and machine learning to solve real-world challenges? At JPMorgan
Chase, we're transforming the way payments work in the Commercial & Investment Bank by leveraging cutting-edge document extraction and natural language processing (NLP) technologies. As a Vice President and Applied AI/ML Lead, you will play a pivotal role in building innovative solutions that enhance trust, safety, and operational efficiency for one of the world's leading financial institutions.
As a Vice President, Applied AI and Machine Learning Lead at JPMorgan
Chase within Payments Technology in the Commercial & Investment Bank, you will lead the delivery of document extraction and natural language processing capabilities that improve trust, safety, and operational effectiveness. You will own solutions end-to-end, from problem framing and data strategy to production deployment and measurement. You will remain hands‑on while setting technical direction and partnering across product, engineering, data, risk, and compliance stakeholders.
- Own end‑to‑end delivery of document extraction and natural language processing solutions, from opportunity sizing and requirements through production rollout and iteration.
- Design scalable model pipelines for document ingestion, text extraction, classification, and ranking, balancing accuracy, latency, throughput, and cost.
- Develop and improve natural language processing algorithms and model approaches to extract entities, relationships, and signals from unstructured text and documents.
- Define evaluation strategies and success metrics, including offline validation, error analysis, robustness testing, and controlled online measurement where appropriate.
- Establish model lifecycle practices including reproducibility, testing, monitoring, drift detection, and incident response to sustain reliable production performance.
- Partner with risk and compliance stakeholders to ensure appropriate documentation, controls, explainability expectations, and audit‑ready processes.
- Drive technical decisions through design reviews, code and model reviews, and pragmatic standards that raise quality and delivery velocity.
- Communicate tradeoffs and recommendations to senior stakeholders, translating model behavior into decision‑ready business impact.
- Formal training or certification on applied artificial intelligence and machine learning concepts and 5+ years applied experience
- 5+ years of experience building and delivering applied machine learning or natural language processing solutions with measurable outcomes in production.
- Strong programming skills in Python and experience using modern machine learning frameworks such as PyTorch or Tensor Flow.
- Hands‑on experience with document extraction and natural language processing techniques including text classification and information extraction.
- Experience designing data‑driven solutions using SQL and distributed processing tools such as Spark or equivalent.
- Experience deploying and operating machine learning services or pipelines in a cloud environment such as Amazon Web Services (or equivalent).
- Demonstrated ability to translate ambiguous business problems into structured machine learning plans, including data strategy, evaluation, rollout, and operationalization.
- Strong communication and collaboration skills, including the ability to explain technical tradeoffs to technical and non‑technical partners.
- Experience with optical character recognition and document understanding workflows for scanned or semi‑structured documents.
- Experience with modern natural language processing architectures such as transformer‑based models and techniques for optimization and efficient inference.
- Experience with machine learning operations practices and tooling, including model registries, continuous integration and delivery for machine learning, and observability.
- Experience with real‑time or event‑driven architectures supporting low‑latency inference and feature generation.
- Experience applying…
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