Applied AI/ML Senior Associate

JPMorgan Chase & Co.; New York; Hybrid; USD 150,000 - 190,000; Full time

Job summary

JPMorgan Chase & Co. Payments is seeking a Senior Associate Applied AI/ML Scientist to advance our AI/ML capabilities across the payments domain. You will design and deploy agentic systems using LLMs, and build scalable data pipelines to improve fraud detection and customer experience.

You will partner with risk, compliance, and cross-functional teams to ensure transparent model documentation and measurable business impact, while keeping pace with state-of-the-art AI developments.

Qualifications

• Master’s degree in a quantitative field with ≥3 years of industry experience.
• Proficiency in Shell Scripting, Jupyter notebook/Lab, SQL, PySpark, and AWS Cloud Services.
• Strong Python skills with ML/DL frameworks (TensorFlow, PyTorch) and libraries (NumPy, Scikit-Learn, Pandas).
• Experience with Jupyter Notebook/Lab is essential.
• Knowledge of agentic systems and tools such as LangChain, LangGraph, MCP, DSPy.
• Solid understanding of ML/AI algorithms, including LLMs and Generative AI.
• Experience in NLP or LLMs, or CV and other ML techniques.

Responsibilities

• Collaborate with Product, Technology, and cross-functional teams to translate business problems into data-driven solutions in payments.
• Design, develop, and deploy agentic systems using LLMs and AI solutions with scalable, low-latency performance.
• Partner with Risk and Compliance to document models, track metrics, and ensure regulatory compliance.
• Translate model outcomes into business impact metrics and communicate with senior management.

Skills

Python

Machine learning

Deep learning

NLP

LLMs

Jupyter

SQL

PySpark

AWS

TensorFlow

PyTorch

NumPy

Scikit-Learn

Pandas

LangChain

LangGraph

Model Context Protocol

DSPy

Education

Master’s degree in a quantitative discipline

Tools

LangChain

LangGraph

Model Context Protocol (MCP)

DSPy

Docker

Kubernetes

DataBricks

Snowflake

Job description

As part of the Commercial & Investment Bank, J.P. Morgan Payments enables organizations of all sizes to execute transactions efficiently and securely, transforming the movement of information, money and assets. We tackle complex challenges at every stage of the payment lifecycle and our industry-leading solutions facilitate seamless transactions across borders, industries and platforms. Operating in over 160 countries and handling more than 120 currencies, we are the largest processor of USD payments, with a daily transaction volume of $10 trillion.

As a Senior Associate Applied AI/ML Scientist within our payment solutions team, you will be instrumental in utilizing artificial intelligence and machine learning technologies to augment our services and stimulate business expansion. Your role will involve researching, experimenting, developing, and implementing high-quality machine learning models, services, and platforms to streamline payment processes, bolster fraud detection, and enrich customer experience. You will also be tasked with designing and executing highly scalable and dependable data processing pipelines, conducting analysis, and deriving insights to boost and optimize business outcomes. Collaborating with cross-functional teams to pinpoint opportunities for AI/ML applications within the payment’s ecosystem will also be a part of your responsibilities.

Job Responsibilities:

• Actively collaborate with Product, Technology, and other cross-functional teams to gain a deep understanding of complex business problems and formulate data-driven solutions to address these challenges in key areas of the payments’ domain.
• Design, develop, and deploy agentic systems using Large Language Models (LLM), machine learning and other AI solutions that meet success metrics aligned with business goals, while considering constraints such as model complexity, scalability, and latency.
• Partner with Risk and Compliance teams to ensure comprehensive model documentation, track performance metrics, and maintain adherence to regulatory compliance standards.
• Translate model outcomes into business impact metrics and communicate complex concepts to senior management and stakeholders.

Required qualifications, capabilities, and skills:

• Master’s degree in a quantitative discipline (e.g., Computer Science, Data Science, Mathematics/Statistics, or Operations Research) with a minimum of 3 years of industry experience. Experience with Shell Scripting, Jupyter notebook/Lab, SQL, PySpark, and AWS Cloud Services is required.
• Proficient in Python with hands-on experience in Machine learning and Deep learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., NumPy, Scikit-Learn, Pandas). Experience with Jupyter Notebook/Lab is essential.
• Extensive knowledge in the design and development of agentic systems and the tooling ecosystem such as LangChain, LangGraph, Model Context Protocol (MCP), DSPy, etc.
• Solid Understanding of algorithms in machine learning, AI, and neural network, including Large Language Models (LLM) and Generative AI as well as familiarity with state-of-the-art practices and advancements in these domains.
• Ability to set the analytical direction for projects, transforming vague business questions into structured analytical plans. You possess strong cognitive and communication skills, characterized by clear and articulate expression. You excel at identifying core issues, bringing order to chaos, synthesizing insights, and driving decisive outcomes.
• Extensive experience in Natural Language Processing (NLP) or Large Language Models (LLM),or Computer Vision and other machine learning techniques, including classification, regression algorithms.

Preferred Qualifications, capabilities and skills

• Experience in the financial services industry, particularly within investment banking operations.
• Cloud computing: Amazon Web Service, Azure, Docker, Kubernetes, DataBricks, Snowflakes.
• Familiarity with inference-time algorithms such as Chain of Thought and sampling, etc.