Lead AI/ML Engineer for AML Risk & LLM Ops

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorgan Chase & Co. in New Jersey seeks a Lead MLE to design, build, and productionize risk-focused ML and LLM solutions for global financial crimes monitoring.

You will lead 4–5 ML engineers and partner with product managers, data scientists, and SREs to deploy scalable models that detect AML risk, regulatory violations, and behavioral anomalies. The role combines risk modeling, NLP architectures, and production-grade engineering with a focus on explainability and auditability.

Qualifications

• 8+ years experience in cloud based applications with 4+ years of experience as an MLE.
• Strong foundation in Information Retrieval, Natural Language Processing and
• Expert in functional programming and JVM based languages- Python, Java

Responsibilities

• Lead a small group of ML engineers
• Lead and influence team with development and operational standards adherence
• Design, build, collaborate, and operate ML models
• Design, build and operate LLM solutions
• Design and build feedback and accuracy measurement techniques for AI solutions
• Design, build and operate risk features data pipelines in Databricks
• Conduct monitoring to detect and alert drift, bias and performance degradation
• Work closely within a cross-functional team following agile based processes
• Collaborate closely with Product Managers, SRE and Compliance SMEs to continuously improve product adoption, reliability and outcomes

Skills

Cloud-based apps

Information Retrieval

Natural Language Processing

Python

Java

ML frameworks

PyTorch

TensorFlow

Scikit-learn

AWS

Databricks

SQL

NoSQL

Messaging stacks

MLOps

Production ML

Distributed systems

Communication

Tools

Databricks

AWS

Java Virtual Machine

Job description

JPMorgan Chase & Co. in New Jersey seeks a Lead MLE to design, build, and productionize risk-focused ML and LLM solutions for global financial crimes monitoring.

You will lead 4–5 ML engineers and partner with product managers, data scientists, and SREs to deploy scalable models that detect AML risk, regulatory violations, and behavioral anomalies. The role combines risk modeling, NLP architectures, and production-grade engineering with a focus on explainability and auditability.