JPMC Candidate Experience pageAbout this role
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 rolloutApply agentic engineering practices to build LLM-powered workflows and evaluate their quality, safety, and reliabilityContribute to deployment workflows including containerization, CI/CD, automated testing, versioning, monitoring, and rollback proceduresDevelop scalable and secure ML/LLM services integrated with strategic platforms and downstream consumersPartner with product, operations, risk and control, and technology teams to clarify requirements and deliver data-led improvementsBuild reusable components such as feature engineering pipelines, evaluation harnesses, and orchestration patternsParticipate in code and design reviews; contribute to best practices, documentation, and team standardsCommunicate with technical and non-technical stakeholders, translating model outputs into practical decisionsMaintain 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 rolesBachelor’s or Master’s degree in a quantitative field or equivalent practical experienceStrong understanding of machine learning fundamentals and applied data analysis skillsExperience designing evaluations and measuring impact in real-world settingsExperience deploying and operating ML models or ML-enabled services in production, including monitoring and troubleshootingStrong Python software engineering skills, including modular code, testing, debugging, and performance awarenessWorking 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 governanceAbility to align evaluation and guardrails to business goals and identify potential unintended outcomesExperience operating in regulated or control-conscious environments with attention to model risk, privacy, security, and audit-ready documentationStrong 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 workflowsFamiliarity with agentic building blocks such as orchestration frameworks and context/memory patterns; awareness of interoperability approachesExperience deploying to AWS (e.g., SageMaker and/or Bedrock) and operating production ML/LLM workloads with attention to cost, latency, performance, security, and scalingExperience integrating human-in-the-loop review and user feedback into iterative improvement, such as labelling strategies, QA workflows, and preference signals
Company:
JPMC Candidate Experience page
Level of experience (years):
Senior (5+ years of experience)
How to apply:
Please mention NLP People as a source when applying