Applied Ai/ml Lead - Payments

JPMorgan Chase JPMorgan Chase · Banking · Seattle, WA +1 · Commercial & Investment Bank

Lead the delivery of document extraction and NLP solutions for payments at JPMorgan Chase. Owns solutions end-to-end, from problem framing and data strategy to production deployment and measurement. Requires strong Python, ML frameworks, SQL, Spark, and cloud deployment experience. Focuses on applied ML and NLP techniques for unstructured text and documents.

What you'd actually do

  1. Own end-to-end delivery of document extraction and natural language processing solutions, from opportunity sizing and requirements through production rollout and iteration.
  2. Design scalable model pipelines for document ingestion, text extraction, classification, and ranking, balancing accuracy, latency, throughput, and cost.
  3. Develop and improve natural language processing algorithms and model approaches to extract entities, relationships, and signals from unstructured text and documents.
  4. Define evaluation strategies and success metrics, including offline validation, error analysis, robustness testing, and controlled online measurement where appropriate.
  5. Establish model lifecycle practices including reproducibility, testing, monitoring, drift detection, and incident response to sustain reliable production performance.

Skills

Required

  • Python
  • PyTorch or TensorFlow
  • SQL
  • Spark
  • Amazon Web Services
  • document extraction
  • natural language processing
  • text classification
  • information extraction
  • model pipelines
  • evaluation strategies
  • model lifecycle practices
  • reproducibility
  • testing
  • monitoring
  • drift detection
  • incident response

Nice to have

  • optical character recognition
  • transformer-based models
  • optimization
  • efficient inference
  • machine learning operations
  • model registries
  • continuous integration and delivery for machine learning
  • observability
  • real-time architectures
  • event-driven architectures
  • low-latency inference
  • feature generation
  • payments
  • financial services
  • regulated environments

What the JD emphasized

  • 5+ years applied experience
  • 5+ years of experience building and delivering applied machine learning or natural language processing solutions with measurable outcomes in production.
  • production deployment
  • operationalization

Other signals

  • end-to-end delivery
  • production deployment
  • model lifecycle practices
  • risk and compliance partnership