JPMorgan Chase

JPMorgan Chase is seeking an Applied AI/ML Vice President to lead the analysis of complex business problems, design and experiment with state-of-the-art models, and develop robust machine learning and deep learning solutions. The role involves applying expertise in ML toolkits and algorithms to identify, build, and deliver solutions with measurable business impact, collaborating with product owners, data engineers, and software engineers to architect and implement new systems and capabilities. Responsibilities include leading AI/ML initiatives, defining roadmaps, developing ML models for NLP, personalization, and recommendation systems, creating end-to-end ML pipelines, and operationalizing model orchestration for use cases like Document Q&A, Search, and classification. The role also requires building batch and real-time prediction pipelines, conducting large-scale data modeling experiments, explaining complex concepts, and deploying solutions into production in collaboration with various partner teams.

Director role focused on applying AI/ML, particularly LLM-driven workflows and agentic systems, within a regulated fintech environment. Responsibilities include setting technical direction, building teams, establishing evaluation and governance practices, and advising on strategy for GenAI solutions.

Executive Director role focused on leading the design and delivery of large-scale recommendation, ranking, and personalization systems for a consumer banking division. The role involves applying ML, including LLMs, to improve customer experiences, leading a team, and ensuring systems are reliable, secure, and scalable. Core focus is on recommenders and personalization, with pragmatic use of GenAI to augment the stack.

Lead and mentor a team of AI/ML engineers in designing, building, and deploying GenAI and LLM applications, including custom model fine-tuning and agentic solutions, within a secure and scalable enterprise environment. Focus on end-to-end development, integration, and production deployment, with responsibilities spanning data pipelines, model evaluation, and architectural roadmapping.

This role focuses on engineering and deploying LLM-based and generative AI applications within a financial institution. It involves developing, deploying, and ensuring the scalability and reliability of AI/ML solutions in production, with a strong emphasis on MLOps practices and utilizing vector databases and cloud platforms like AWS.

Director role focused on applying AI/ML, particularly LLM-driven workflows and agentic systems, within a regulated fintech environment. Responsibilities include setting technical direction, building teams, establishing evaluation and governance practices, and advising on strategy for GenAI solutions.

Lead the design, build, and deployment of end-to-end AI solutions, focusing on LLMs and agentic systems for business insights in a financial services context. This role involves advanced applied research, AI engineering, and data science expertise, with a strong emphasis on leading technical teams and driving complex initiatives.

JPMorgan Chase is seeking an Applied AI/ML Senior Associate Machine Learning Engineer to join their Commercial & Investment Bank team. The role involves combining AI techniques with financial data to optimize business decisions and automate processes. Responsibilities include building scalable data science capabilities, deploying ML services, researching datasets, communicating AI capabilities, documenting processes for regulatory compliance, and collaborating on production architectures. The position requires a Masters or PhD in a quantitative discipline, strong ML theory, NLP specialization, MLOps knowledge, PyTorch experience, and cloud provider familiarity. Experience with containerization and model monitoring is also expected.

Lead Applied AI/ML Engineer at JPMorgan Chase in London, focused on building and deploying AI-powered products for the Commercial & Investment Bank. The role involves leveraging NLP and Computer Vision to optimize business decisions and automate processes, requiring a blend of research and software engineering skills, with a focus on productionizing ML models and services.

Director level role focused on engineering and scaling GenAI capabilities, specifically agentic workflows and RAG systems, within an enterprise setting. The role involves building reusable frameworks, shared components, and establishing best practices for production-grade AI solutions, with a strong emphasis on evaluation, monitoring, and governance. The position requires deep software and data engineering expertise, cloud-native experience, and the ability to translate complex technical concepts to senior stakeholders.

Lead the design and delivery of human-in-the-loop (HITL) interfaces for supervising and steering AI agents in financial operations, focusing on production-grade web applications with React and TypeScript, and integrating with agentic workflows.

Executive Director Principal Software Engineer to lead the design, build, and scaling of a next-generation multi-agent AI platform within the Corporate and Investment Bank Technology – Securitized Product Group Technology team. The role involves writing production code, owning architectural decisions, unblocking engineers, and setting multi-year strategy. Responsibilities include owning agentic platform strategy (toolchains, RAG, memory, context, evaluation, feedback loops), architecting multi-agent systems with frameworks like LangChain/LangGraph/AutoGen, designing distributed ingestion/workflow systems, establishing standards for the agentic development lifecycle, contributing directly in Python, leading reviews, and building reusable agent components.

Senior Principal Software Engineer focused on LLM Engineering within JPMorgan Chase's Trust & Safety Fraud Prevention team. The role involves architecting, building, and optimizing model serving solutions, particularly for LLMs and GNNs, across cloud and on-premises environments. Key responsibilities include defining MLOps/LLMOps strategies, driving inference optimization for high throughput and low latency, creating reusable ML engineering frameworks, and ensuring observability, reliability, and cost efficiency in production AI workloads.

Director of ML Engineering to lead the technical vision and execution for a core Agent SDK and the agentic systems it enables, focusing on building and scaling foundational toolkits for enterprise AI.

Executive Director role focused on architecting and leading the development of next-generation AI/ML solutions for credit card and banking business decisions, managing the full AI/ML lifecycle from design to production deployment, and leading a team of AI/ML scientists and engineers. Emphasizes deep learning, advanced modeling, MLOps, and cloud-native deployment within a regulated financial services environment.

Lead Data Scientist at JPMorgan Chase, responsible for building and deploying secure, scalable, production-grade AI/ML solutions, with a focus on generative AI applications and operating within regulated environments. This role involves applied research, model development, MLOps, and mentoring.

Lead a team of AI/ML scientists and engineers to design, develop, and deploy AI/ML solutions for market operations in a large financial institution. Focus on end-to-end delivery, production deployment, MLOps, and stakeholder engagement.

Senior Associate role focused on developing and implementing GenAI and Agentic AI solutions for financial services, involving data collection, model experimentation, deployment, and stakeholder communication. The role emphasizes applying LLMs and ML techniques to solve business problems and enhance client services.

As an Applied AI/ML Vice President in the AI for Operations organization at JPMorgan Chase, this role focuses on designing, building, and scaling NLP solutions to improve customer and internal agent experiences. The position involves hands-on work across the model lifecycle, translating operational needs into production-grade language capabilities like intelligent search, summarization, classification, and next-best-action recommendations. The role emphasizes applying technical judgment to choose appropriate methods (including LLMs), evaluating performance, and ensuring solutions are reliable, secure, and scalable.

Executive Director for Applied AI/ML in AI for Operations at JPMorgan Chase, focusing on designing, building, and scaling cutting-edge NLP solutions for customer and internal agent experiences. The role involves applying LLM-based methods, rigorous metrics, and ensuring solutions are reliable, secure, and scalable. Responsibilities include full product development lifecycle, advanced analytics, and system development in NLP and machine learning, with a focus on intelligent search, summarization, classification, and next-best-action recommendations.

Machine Learning Engineer focused on applying LLMs and AI to document digitization within a financial services context. Responsibilities include the full ML lifecycle from training to deployment and monitoring, building scalable pipelines, and ensuring security and compliance.

As an Applied AI/ML Senior Associate in the AI for Operations organization, this role focuses on designing, building, and scaling NLP solutions for customer and internal agent experiences within a financial services context. Responsibilities include analyzing data, developing models, ensuring reliability and scalability, and mitigating risks associated with ML systems, particularly LLMs for tasks like search, summarization, and classification.

Lead Applied AI/ML Scientist role focused on developing and deploying agentic systems using LLMs and other AI solutions for payment processes, fraud detection, and customer experience enhancement within a financial services context. Requires strong Python, ML/DL framework, and agentic system tooling experience, with a focus on scalability, regulatory compliance, and translating model outcomes into business impact.

Product Manager (VP level) for Conversational AI within JPMorgan Chase's Machine Learning and Optimization team. The role involves defining AI/ML/NLP product strategy, leading projects from concept to delivery, and incorporating advancements in Gen AI, agentic systems, LLMs, and deep learning. Responsibilities include creating and tracking conversational AI metrics, collaborating with data annotation teams for training and evaluation data, managing the product backlog, and leading agile scrum teams. Requires expert-level NLP/ML experience, particularly in deep learning, LLMs, and agentic systems, with a proven ability to build large-scale AI systems and lead cross-functional teams.

Vice President role focused on building, deploying, and governing production AI/ML models, including LLMs and generative AI systems, within a large financial institution. The role emphasizes model governance, monitoring, and leveraging generative AI for productivity and efficiency, with a strong focus on regulatory compliance and cross-functional leadership.

Vice President role in AI for Operations at JPMorgan Chase, focusing on designing, building, and scaling NLP solutions for customer and internal agent experiences. The role involves applying LLM-based methods, evaluating performance, and ensuring solutions are reliable, secure, and scalable. Responsibilities include full product development lifecycle, advanced analytics, and contributing to continuous learning.

Develop and implement GenAI and Agentic AI solutions using Python to enhance automation and decision-making processes within a Private Bank setting. This role involves analyzing existing processes, designing autonomous AI agents, applying LLMs and ML techniques, and collaborating with stakeholders to solve complex business challenges through cloud-centric software delivery.

As an Applied AI/ML Senior Associate in the AI for Operations organization at JPMorgan Chase, this role focuses on designing, building, and scaling cutting-edge Natural Language Processing (NLP) solutions to improve customer and internal agent experiences within the Consumer & Community Banking division. The role involves applying LLM-based methods and advanced analytics to solve complex business problems, working across the full model lifecycle from defining objectives to production deployment, and contributing to operational workflows through intelligent search, summarization, classification, and next-best-action recommendations.

This role focuses on designing, building, and productionizing Generative AI and Agentic AI solutions, including LLM/SLM-powered applications like RAG, summarization, chat experiences, and tool-using agents. It requires strong software engineering skills in Java/Python, API development, MLOps, and cloud deployment on AWS, with an emphasis on secure coding, reliability, and automated evaluation.

Associate Senior Data Scientist at JPMorgan Chase in Bengaluru, focusing on designing, deploying, and managing prompt-based LLM models for NLP tasks in financial services. The role involves prompt engineering, LLM orchestration, building data pipelines, and developing tools for model training and evaluation, with a requirement for Python, PyTorch/TensorFlow, cloud platforms, and MLOps.

Vice President in the CIB Technology team at JPMorgan Chase, focusing on analyzing business problems, experimenting with state-of-the-art models, and developing machine learning and deep learning solutions. The role involves leading AI/ML initiatives, defining roadmaps, developing models for NLP, personalization, and recommendation systems, and operationalizing end-to-end ML pipelines for use cases like Document Q&A, Search, and Information Retrieval. It also includes building batch and real-time prediction pipelines, collaborating with various teams for production deployment, and working with LLMs and Gen AI solutions.

Lead the design, development, and deployment of advanced AI, GenAI, and large language model solutions, acting as a subject matter expert and collaborating with cross-functional teams to deliver scalable, production-ready AI systems. This role involves end-to-end Python development, integrating generative AI, driving adoption of ML infrastructure, optimizing performance, and ensuring responsible AI practices and governance within a fintech domain.

Principal AI/ML Engineer at JPMorgan Chase focused on building and operating LLM-powered APIs and agentic AI systems. The role involves designing agent architectures, writing production code, creating reusable components, managing the end-to-end ML lifecycle, optimizing inference, and embedding responsible AI practices. Requires strong Python, LLM/agentic AI experience, MLOps, and cloud deployment skills.

Lead Generative AI Engineering role focused on designing, delivering, and improving production generative AI products and reusable backend APIs for firmwide adoption. This hands-on leadership position involves architecting scalable systems, setting technical direction for model-enabled services, ensuring reliability and responsible AI controls, and mentoring engineers. The role operates in production environments, emphasizing building at scale and driving execution against measurable outcomes.

Director-level role focused on defining and implementing governance frameworks for agentic AI within a financial services context. The role involves establishing risk management, oversight, and best practices for multi-agent systems and autonomous AI, aiming to accelerate safe AI deployment and position the company as an industry leader. Requires deep technical understanding of AI/ML, agentic systems, and regulatory landscapes.

This role focuses on designing, building, and supporting production generative AI products and reusable backend APIs within a large enterprise. It involves combining enterprise data with LLMs and multimodal models to deliver scalable, measurable solutions, collaborating with ML, cloud, and SRE teams, and ensuring reliability, performance, and operational controls. The role emphasizes hands-on engineering, real-world constraints, and high-impact delivery.

Lead Software Engineer focused on AI/ML and Infrastructure as Code (IaC) within a financial services technology team. The role involves designing, developing, and deploying AI/ML models and agent-based systems for automation, including IaC development, CI/CD enhancement, and AI-powered observability. Requires strong experience in AI/ML engineering, agent-based systems, IaC automation, observability tools, and programming languages like Python or Java.

Lead AI/ML Engineer (VP level) at JPMorgan Chase, focusing on designing and delivering enterprise-scale AI/ML solutions, particularly LLM-based systems and agent workflows. The role involves hands-on coding, setting engineering standards, defining architectural patterns, and ensuring production readiness with strong observability and operational rigor. It emphasizes building Copilot-integrated solutions and managing the AI/ML lifecycle.

Lead engineer to build and deploy generative AI, agentic AI, and LLM solutions, focusing on context engineering, semantic modeling, and unified semantic layers within a regulated financial services environment. This role involves end-to-end development from proof-of-concept to production, including data pipelines, model training, evaluation, and responsible AI practices.

JPMorgan Chase is seeking a Quant Modeling Senior Associate with 5+ years of experience in data science, machine learning, or AI to join their Investment Risk & Analytics team. The role involves designing, developing, and deploying advanced AI/ML models, including generative AI and deep learning, for risk quantification and strategic decision-making. Responsibilities include the full AI/ML lifecycle, risk modeling, scenario analysis, and mentoring junior staff. Requires a strong background in statistics, mathematics, and programming in Python, with experience in investment products and data visualization.

Principal Software Engineer at JPMorgan Chase focused on designing, implementing, and scaling AI/ML infrastructure and platforms on AWS. The role involves collaborating with teams, developing and optimizing ML models, leveraging Databricks, and leading the productionalization of Gen AI use cases. Requires strong experience in AI/ML engineering, LLM Ops, model serving, and fine-tuning.

This VP AI/ML Data Scientist role focuses on translating complex banking challenges into production-grade AI/ML and LLM solutions, including building intelligent agents and LLM-based systems for various banking use cases. The role involves end-to-end pipeline ownership, MLOps implementation, and ensuring governance and compliance in a regulated environment.

Lead an applied AI/ML team within a financial services context, focusing on developing and productionizing scalable, trustworthy, and explainable solutions. Responsibilities include defining technical vision, managing ML workflows, and applying expertise in areas like LLMs, NLP, RL, and advanced ML techniques including inference, fine-tuning, RAG, and prompt engineering. The role requires hands-on experience and leadership in building and operating AI/ML solutions.

Software Engineer III - Applied AI at JPMorgan Chase, focused on developing and deploying generative AI applications and agents, with expertise in MLOps, AWS, and integrating user feedback for self-improving systems within the fintech domain.

Lead Software Engineer for JPMorgan Chase's Consumer & Community Banking division, focusing on designing and building critical technology solutions for Chase AI components like Chase Agent, Agent Operating Memory, Domain Agents, Agentic Experience Service, and Assurance. The role involves creating secure, high-quality production code, executing software solutions, producing architecture and design artifacts, and troubleshooting complex problems. Key responsibilities include adopting new technologies for agentic solutions, collaborating with cross-functional teams, leading code reviews, mentoring junior engineers, and ensuring compliance with security, privacy, and regulatory requirements. Requires hands-on experience building agentic systems using LLMs/SLMs, proficiency in Java/Python, experience with Spring AI or Python frameworks, AWS, and understanding of LLM patterns like function calling, RAG, and safety guardrails.

Lead Data Scientist role focused on applying NLP and LLM expertise to develop business-centric AI solutions for investment processes, client experiences, and operations within JPMorgan Asset Management. The role involves extracting insights from financial data, building AI solutions for content extraction, search, Q&A, reasoning, and recommendation, and collaborating with engineering for scalable delivery.

Principal Architect role focused on designing and delivering production-grade Generative AI and LLM systems, including agentic workflows, for financial services. Requires strong software engineering and ML engineering experience with cloud platforms and various programming languages and frameworks.

Principal AI/ML and Gen AI Engineer at JPMorgan Chase focused on scaling AI/ML infrastructure and platforms for model serving and fine-tuning, with expertise in LLM Ops and productionalizing Gen AI use cases on AWS and Databricks.