Senior AI/ML Engineer — Secure Production ML

Aumni; Jersey City (NJ); On-site; USD 140,000 - 190,000; Full time

Job summary

JPMorganChase is seeking a Software Engineer III - AI/ML Engineer to join the AI For Technology group in a fast-paced agile environment. You will design and deliver trusted AI/ML solutions that power multiple business functions while ensuring security, stability, and scalability.

You will transform business requirements into AI/ML specifications, contribute to architecture and design artifacts, and drive continuous improvement of software applications and data pipelines using state-of-the-art

Qualifications

• Formal training or certification in software engineering concepts and 3+ years applied experience.
• Hands-on practitioner of production AI/ML solutions.
• Experience with agentic workflows and frameworks (LangChain, LangGraph, Auto-GPT).
• Deep knowledge of machine learning and AI fundamentals.

Responsibilities

• Deliver AI/ML projects through the ML development life cycle using Agile methodology.
• Execute solutions and designs with advanced problem solving and troubleshooting.
• Create secure, high-quality production code and maintain algorithms.
• Produce architecture and design artifacts for complex applications.
• Analyze large data sets to visualize and report for system improvements.
• Identify data patterns to improve coding hygiene and architecture.
• Contribute to software engineering communities of practice.

Skills

AI/ML development

Python

Distributed computing

AWS cloud

CI/CD

Education

Formal training or certification in software engineering

Tools

LangChain

LangGraph

Auto-GPT

TensorFlow

PyTorch

Keras

scikit-learn

NumPy

Spark

Dask

Job description

JPMorganChase is seeking a Software Engineer III - AI/ML Engineer to join the AI For Technology group in a fast-paced agile environment. You will design and deliver trusted AI/ML solutions that power multiple business functions while ensuring security, stability, and scalability.

You will transform business requirements into AI/ML specifications, contribute to architecture and design artifacts, and drive continuous improvement of software applications and data pipelines using state-of-the-art