Join us at the forefront of payments innovation, where your expertise in machine learning and generative AI will help shape how money moves worldwide. You will collaborate with diverse teams to deliver impactful solutions, advancing your career in a dynamic and fast-evolving environment. We value your creativity, technical skills, and drive to make a measurable difference. At JPMorganChase, you’ll find opportunities for growth, learning, and meaningful contribution. Together, we’re building the future of payments.
As an Associate Machine Learning Data Scientist in Payments Machine Learning, you will design, develop, and deploy machine learning applications—including generative AI—on cloud infrastructure. You will contribute across the project lifecycle, partnering with senior engineers and data scientists to ensure solutions are reliable, secure, and observable in production. You will communicate progress and results to stakeholders, maintain clear documentation, and help drive innovation in payments and banking operations.
Job Responsibilities:
- Deliver machine learning and AI solutions for payments and banking operations, from discovery to production rollout
- Apply agentic engineering practices to build LLM-powered workflows and evaluate their quality, safety, and reliability
- Contribute to deployment workflows including containerization, CI/CD, automated testing, versioning, monitoring, and rollback procedures
- Develop scalable and secure ML/LLM services integrated with strategic platforms and downstream consumers
- Partner with product, operations, risk and control, and technology teams to clarify requirements and deliver data-led improvements
- Build reusable components such as feature engineering pipelines, evaluation harnesses, and orchestration patterns
- Participate in code and design reviews; contribute to best practices, documentation, and team standards
- Communicate with technical and non-technical stakeholders, translating model outputs into practical decisions
- Maintain documentation such as model cards, runbooks, experiment notes, and operational procedures
Required Qualifications, Capabilities, and Skills:
- Relevant industry experience in applied machine learning, data science, ML engineering, or related roles
- Bachelor’s or Master’s degree in a quantitative field or equivalent practical experience
- Strong understanding of machine learning fundamentals and applied data analysis skills
- Experience designing evaluations and measuring impact in real-world settings
- Experience deploying and operating ML models or ML-enabled services in production, including monitoring and troubleshooting
- Strong Python software engineering skills, including modular code, testing, debugging, and performance awareness
- Working knowledge of ML engineering/MLOps concepts, including training vs. serving, batch vs. real-time, orchestration, scalable data processing, and familiarity with model/prompt versioning and governance
- Ability to align evaluation and guardrails to business goals and identify potential unintended outcomes
- Experience operating in regulated or control-conscious environments with attention to model risk, privacy, security, and audit-ready documentation
- Strong stakeholder management and teamwork skills, with the ability to drive outcomes in cross-functional teams
Preferred Qualifications, Capabilities, and Skills:
- Hands-on experience with NLP and/or generative AI, including LLMs, RAG, tool/function calling, and agentic workflows
- Familiarity with agentic building blocks such as orchestration frameworks and context/memory patterns; awareness of interoperability approaches
- Experience deploying to AWS (e.g., SageMaker and/or Bedrock) and operating production ML/LLM workloads with attention to cost, latency, performance, security, and scaling
- Experience integrating human-in-the-loop review and user feedback into iterative improvement, such as labelling strategies, QA workflows, and preference signals
About UsJ.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
Skills Required
- Relevant industry experience in applied machine learning, data science, ML engineering, or a related role
- Bachelor’s or Master’s degree in a quantitative field, or equivalent practical experience
- Strong understanding of machine learning fundamentals and applied data analysis
- Experience designing evaluations and measuring impact in real-world settings
- Experience deploying and operating machine learning models or ML-enabled services in production, including monitoring and troubleshooting
- Strong Python software engineering skills, including modular code, testing, debugging, and performance awareness
- Working knowledge of ML engineering and MLOps concepts, including training versus serving, batch versus real-time processing, orchestration, scalable data processing, model versioning, prompt versioning, and governance
- Ability to align evaluations and guardrails with business goals and identify potential unintended outcomes
- Experience operating in regulated or control-conscious environments with attention to model risk, privacy, security, and audit-ready documentation
- Strong stakeholder management and teamwork skills, with the ability to drive outcomes in cross-functional teams
- Hands-on experience with NLP or generative AI, including LLMs, RAG, tool or function calling, and agentic workflows
- Familiarity with agentic building blocks, orchestration frameworks, context and memory patterns, and interoperability approaches
- Experience deploying to AWS, including SageMaker or Bedrock, and operating production ML or LLM workloads
- Experience integrating human-in-the-loop review and user feedback into iterative improvement, including labeling strategies, QA workflows, and preference signals
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
-
Healthcare Strength — Medical, dental, vision, and mental-health coverage are broad, with wellness incentives, on-site or virtual care, and an EAP offering coaching and counseling. Plan materials emphasize accessible options, including multiple medical choices and tools to manage costs.
-
Parental & Family Support — Paid parental leave extends up to 16 weeks for all parents, supplemented by paid Critical Caregiver Leave. Family resources include backup childcare via Bright Horizons, lactation support and milk-shipping, family-building assistance, and even a free five-month SNOO rental for newborns.
-
Retirement Support — Retirement programs include a 401(k) with an annual company match and automatic pay credits for most employees, with a legacy pension available to earlier hires. An Employee Stock Purchase Plan at a 5% discount further supports long-term savings.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
Gallery







