JPMorgan Chase

Develops and deploys AI/ML models and generative AI solutions within web platforms and reporting tools for a financial services company, focusing on improving data delivery and user experience. The role involves mentoring other developers and integrating AI into existing analytics platforms.

Software Engineer III - AI/ML Engineer at JPMorganChase within the AI For Technology group, responsible for delivering AI/ML projects through the ML development life cycle using Agile methodology. The role involves transforming business requirements into AI/ML specifications, designing and developing production AI/ML solutions, and creating secure, high-quality production code. Familiarity with agentic workflows and expertise in areas like LLMs, NLP, Knowledge Graph, Computer Vision, Speech Recognition, RL, Ranking/Recommendation, or Time Series Analysis is required.

Lead Software Engineer role focused on integrating AI/ML techniques, including LLMs and Generative AI, into production software systems within a financial services context. The role involves leading a team, architecting solutions, and developing secure, scalable AI-driven software.

Lead Software Engineer for AI/ML Data Platforms at JPMorgan Chase, focusing on building production-grade AI/ML applications and Generative AI agents. The role involves advancing experiments, developing scalable platforms, and ensuring operational stability, primarily serving AI Research and MLCoE teams within a fintech domain.

Senior Director of Software Engineering for AI Infrastructure Platform at JPMorgan Chase, leading multiple departments to deliver a unified AI infrastructure layer across on-premises, public cloud, and accelerated-compute vendors. Owns training and experimentation on a Kubernetes-standardized platform, acting as a design partner for architectural trade-offs and ensuring reliable, secure, and operable systems at enterprise scale. Responsibilities include standardizing AI developer workflows, building platform APIs, improving GPU availability and utilization, defining scheduling and placement strategies, embedding security and controls, driving operational excellence, and leading engineering teams.

The Quant Modeling Lead - Vice President role within JPMorgan Chase's Model Risk Governance and Review (MRGR) team focuses on the independent validation and risk governance of forecasting and scoring models, including those using advanced AI/ML techniques, for consumer banking applications. The role involves evaluating model conceptual soundness, performing independent testing, monitoring performance, and liaising with various internal and external stakeholders, including regulators.

Lead the design and delivery of AI/ML solutions for Market Operations at JPMorgan Chase. This role involves managing a team, partnering with business and technology stakeholders, and ensuring the successful implementation and scaling of AI-driven tools. The focus is on developing and deploying production-grade AI/ML applications, establishing best practices for evaluation and monitoring, and driving measurable impact.

ML Ops Engineer role focused on deploying, monitoring, and managing machine learning models in production environments within JPMorgan Chase's Cybersecurity team. Responsibilities include building CI/CD pipelines, optimizing infrastructure, and ensuring reliable and efficient AI system performance.

This role focuses on applying and scaling AI/ML solutions, particularly LLM-based methods and AI Agents, within a financial services context. The engineer will build and scale ML platforms, ensure solutions are reliable and secure, and contribute to production model monitoring and iteration.

Executive Director leading a team of AI/ML scientists to build and deploy advanced geospatial, graph-based, and network optimization models for branch network strategy. The role involves stakeholder management, translating innovations into production solutions, establishing best practices, and overseeing model validation and monitoring within a regulated financial services environment.

Develop and launch AI/ML models for consumer banking, focusing on retail network optimization, investment, and workforce effectiveness using geospatial AI, graph-based models, and reinforcement learning. This VP-level role requires end-to-end project leadership, stakeholder management, and translating technical outputs for business partners, while ensuring regulatory compliance.

Lead Software Engineer for Commercial and Investment Banking team, focusing on researching, developing, and productionizing high-performance machine learning and quantitative models, and designing scalable data processing pipelines. Requires deep ML/DL knowledge and experience with frameworks like TensorFlow/PyTorch, and ETL/real-time data processing.

JPMorgan Chase is seeking a Vice President to lead the strategic vision and execution of AI/ML and Agentic AI initiatives within their Client 360 Technology Organization. This role involves defining the Data Science agenda, steering modeling and analytical efforts, and collaborating with various business and technology partners to leverage data insights and create business value. The position requires deep data science expertise, strong quantitative skills, and leadership abilities to build and manage global analytical teams.

Quantitative Trading & Research team at JPMorgan Chase seeks an Associate/Vice President to apply AI/ML techniques, including LLMs and sequential decision-making models, to transform business operations in Securities Services, Payments, and CIB Treasury. The role involves end-to-end project management, from data architecture to model development and stakeholder presentations, focusing on revenue growth and efficiency.

Principal Software Engineer at JPMorgan Chase within the Finance Technology team, responsible for building scalable applications using Generative AI to drive innovation and business value. Requires expertise in software engineering, Data Mesh architecture, and cloud-native practices.

Lead Data Scientist role focused on building GenAI applications, virtual assistants, and workflow automations using multi-agent AI patterns within the Payments domain. Responsibilities include translating business problems into end-to-end AI solutions, designing prompts, and driving iterative development and production monitoring of these solutions.

Machine Learning Engineer - Senior Associate at JPMorgan Chase focused on designing, developing, and maintaining AIOps solutions. The role involves integrating AI/ML capabilities, particularly LLM techniques like Agents, Planning, and Reasoning, into software applications. Experience with Ranking, Recommender systems, RAG, and Agent systems is required, along with strong Python programming and cloud platform skills.

JPMorgan Chase is seeking an Applied AI/ML Senior Associate to analyze business problems, experiment with state-of-the-art models, and develop machine learning and deep learning solutions. The role involves developing end-to-end ML/AutoML/AutoNLP pipelines, operationalizing ML models for use cases like Document Q&A, Search, Information Retrieval, classification, and personalization. The candidate will build batch and real-time prediction pipelines, collaborate with various teams for production deployment, and work with LLMs and Gen AI solutions.

Senior Director of Software Engineering at JPMorgan Chase leading the enterprise data platform strategy, focusing on data engineering, governance, AI enablement, and agent-based workflow automation. The role involves owning the platform roadmap, ensuring security, compliance, and scalability, and enabling teams to leverage trusted data products and responsible AI.

Quantitative Trading & Research team at JPMorgan Chase seeks an Associate/VP to apply AI/ML techniques, including LLMs and sequential decision making, to transform business operations in Securities Services, Payments, and CIB Treasury. The role involves end-to-end project management, from data processing and analysis to model development and presenting commercial recommendations.

Quantitative Researcher (VP) at JPMorgan Chase focusing on Derivatives Modelling, Financial Engineering, and Data Science to enhance risk and pricing analytics for the Clearing business. The role involves leading the design, delivery, and governance of models, including Initial Margin methodology, and applying machine learning to transform risk management and automation. Responsibilities include end-to-end initiative leadership, model ownership, building and productionizing analytics, and leading ML/AI solution development.

Lead Security Engineer focused on AI/ML security, red teaming, and adversarial resilience for generative AI, RAG pipelines, and ML systems within a large enterprise. Responsibilities include developing security strategies, designing secure architectures, reducing vulnerabilities, conducting threat modeling, and implementing AI red teaming methodologies.

Machine Learning Engineer (VP) at JPMorgan Chase focused on designing, developing, and deploying AI-powered document digitization solutions using LLMs and generative AI. The role involves managing the end-to-end ML lifecycle, building scalable pipelines on AWS, and ensuring security and compliance within a financial services context.

This role focuses on managing AI controls within a financial institution, involving technical risk assessments of AI/ML use cases, evaluating model design, data quality, and potential failure modes. The manager will also develop and implement AI governance frameworks, policies, and control standards, and perform deep-dive technical reviews of AI solutions. The role requires strong Python skills, understanding of ML concepts, and the ability to translate complex AI technical concepts for non-technical stakeholders. Experience with GenAI/LLMs and financial services is preferred.

Seeking an AI engineer to develop and productionize NLP models and services for bank operations, focusing on end-to-end projects and scalable data pipelines.

This role focuses on integrating AI/ML capabilities into software applications, with a key focus on AIOps. The candidate will design, develop, and maintain these applications, collaborate with cross-functional teams, and implement AI/ML models into production. Experience with LLM techniques, agents, RAG, recommender systems, and large datasets is required.

Lead Data Scientist for Workforce Planning at JPMorgan Chase, focusing on developing and deploying AI/ML models for forecasting, capacity planning, and scheduling. The role involves full model lifecycle management, project leadership, stakeholder collaboration, and mentoring junior team members, with an emphasis on moving towards real-time inference and decision-making.

Lead Software Engineer focused on AI/ML Deep Learning and GPU ML Serving within a Commercial and Investment Banking team. Responsibilities include designing, developing, and troubleshooting software solutions, writing production code, producing architecture artifacts, analyzing data, and optimizing deep learning models for inference. The role requires experience with ML systems, Python, ML frameworks, cloud technologies (Docker, Kubernetes), ML model serving frameworks, GPU workloads, low-latency systems, and NoSQL databases. Experience with GPU resource management and microservices architecture is also needed. Preferred qualifications include an advanced degree, proficiency in multiple programming languages, experience with graph neural networks, GPU programming, model monitoring, MLOps tools, and serving large-scale models.

Software Engineer III at JPMorgan Chase focused on AI/ML Deep Learning and GPU ML Serving. The role involves developing, testing, and troubleshooting software solutions, writing production code, producing architecture artifacts, analyzing data, and optimizing deep learning models for production inference. Key responsibilities include deploying and managing GPU workloads in Kubernetes, building scalable, low-latency systems, and partnering with product teams. Requires formal training/certification, 3+ years of applied experience, proficiency in Python and ML frameworks, experience with cloud technologies (Docker, Kubernetes, EKS), ML model serving frameworks, GPU workloads in Kubernetes, and NoSQL databases. Familiarity with modern microservices architecture and leading large-scale system design is also needed. Preferred qualifications include an MS/PhD, Java proficiency, experience with graph neural networks, GPU programming, model monitoring, MLOps tools, and serving large-scale models.

Build AI agentic workflows and machine learning models for risk monitoring, signal generation, and forecasting in a quantitative trading environment. Develop real-time data pipelines and deliver actionable insights to traders and risk partners.

Principal Software Engineer focused on High-Performance Computing (HPC) to optimize AI/ML model training and inference. The role involves creating scalable coding frameworks, developing production code, advising cross-functional teams, and publishing patterns for ML model optimization on various architectures. Requires deep experience in HPC, accelerators, deep learning (LLMs), and AI/ML frameworks, with a focus on performance and scalability for financial services.

JPMorgan Chase is seeking an AI Analytics Solutions Manager with 6+ years of experience in AI/ML development, GenAI, and LLMs. The role involves hands-on coding for production solutions, owning end-to-end code development, and implementing AI strategies. Requires experience with AI/ML frameworks (TensorFlow, PyTorch), cloud AI services, Python/R, and advanced prompting strategies. Experience with NLP, computer vision, and deploying models in production is preferred. The role focuses on integrating AI technologies, ensuring scalability, performance, security, and implementing technology risk controls within a regulated financial environment.

JPMorgan Chase is seeking a Data Scientist Associate for their APAC Payments Data & Analytics team. The role focuses on delivering high-impact AI & Analytics use cases, driving data strategy, and creating data-driven products for clients and internal partners. Responsibilities include exploring money movement, forging partnerships with stakeholders, identifying and integrating Agentic AI workflows, and collaborating with product managers. Requires 4+ years of experience in Data Science, Analytic Solutions, and GenAI/Agentic AI use cases, with expertise in data platforms (Databricks, PySpark, Tableau) and cloud platforms (AWS). Familiarity with LLMs, prompt engineering, and RAG/MCP integrations is essential. Experience in payments or consulting is preferred.

Lead Software Engineer on the Transformative AI Team at JPMorgan Chase, focused on building an Agentic Private Bank using GenAI and LLMs. The role involves designing, developing, and deploying AI solutions, including prompt-based models and data pipelines, within a financial services context.

Lead Software Engineer focused on building and deploying AI/ML platform infrastructure on AWS for model deployment at scale within a financial institution. The role involves developing APIs for automated retraining, scheduling, endpoint deployments, and autoscaling, as well as implementing model monitoring solutions, with a specific emphasis on LLM monitoring and automated issue correction. The engineer will also engage with clients for support and contribute to disaster recovery and multi-region capabilities.

Principal Software Engineer at JPMorgan Chase within Corporate Technology, focusing on building and enhancing Machine Learning platforms for deploying predictive models at scale. The role involves architecting, designing, and integrating solutions within a large enterprise environment, establishing standards for the ML Platform, and optimizing ML libraries and frameworks. Requires expertise in Java & Spring Boot, ML frameworks, Big Data technologies (Spark, Hadoop), and cloud platforms (Azure, AWS, Databricks).

Senior Lead Software Engineer role focused on developing intelligent agent-based systems and optimizing data pipelines on Databricks, leveraging Java and Python. The role involves designing, training, and deploying AI agents, mentoring team members, and collaborating with cross-functional teams in an enterprise environment with AWS cloud experience.

Senior Manager of Software Engineering for Machine Learning & Cloud within the Corporate Technology - Consumer & Community Bank Risk group at JPMorgan Chase. The role involves leading a team of 10, mentoring technical teams, and driving the development and productionization of ML models using cloud services and MLOps practices. Responsibilities include technical leadership, code development, troubleshooting, and managing ML pipelines.

Lead Software Engineer role focused on designing and building critical technology solutions for Chase AI components, including agentic systems, using LLMs/SLMs. Requires strong software engineering experience, proficiency in Java/Python, cloud technologies (AWS), API design, and practical understanding of LLM patterns like function calling, RAG, and guardrails. The role emphasizes building secure, high-quality production code and contributing to agentic solutions.

Lead Software Engineer at JPMorgan Chase within the Consumer & Community Banking (CCB) division, responsible for designing and building critical technology solutions across Chase AI components, including Chase Agent, Agent Operating Memory, Domain Agents, Agentic Experience Service, and Assurance. The role requires hands-on experience building agentic systems using LLMs/SLMs and proficiency in various programming languages and cloud technologies.

Lead Software Engineer role focused on designing and building critical technology solutions for Chase AI components, including agentic systems, using LLMs/SLMs. Requires strong software engineering experience, proficiency in Java/Python, cloud technologies (AWS), API design, and practical understanding of LLM patterns like function calling, RAG, and guardrails. The role emphasizes building secure, high-quality production code and contributing to agentic solutions.

Develop AI/ML solutions for the Credit Card business, focusing on applying foundation models and Generative AI. Responsibilities include defining business problems, scoping solutions, implementing and evaluating GenAI-based methods, and collaborating with stakeholders. Requires experience with GenAI, prompt engineering, and LLM-enabled applications.

Senior Lead Software Engineer at JPMorgan Chase focused on building and enhancing technology products. The role involves providing technical guidance, developing secure production code, influencing product design, and acting as a subject matter expert. Requires experience in machine learning, NLP, training/fine-tuning LLMs, transformer architectures, and deploying AI systems, with proficiency in Python, TensorFlow, or PyTorch. Experience with scalable distributed systems, cloud-native environments, and security protocols is also necessary.

Software Engineer II - Applied AI at JPMorgan Chase in London. This role focuses on developing and deploying advanced machine learning models and generative AI applications/agents, with a strong emphasis on MLOps, AWS deployment, and integrating user feedback for self-improving systems. The role involves architecting AI solutions, analyzing data, ensuring scalability and reliability, and staying updated on AI advancements.

Lead Software Engineer to build and maintain production-grade ML pipelines and infrastructure at enterprise scale for JPMorgan Chase's MLCOE. This role focuses on designing, developing, and deploying end-to-end ML systems, from data ingestion to serving outputs, with a strong emphasis on AWS services, CI/CD, and performance monitoring.

Lead Software Engineer role focused on building and deploying production-grade machine learning pipelines and systems at enterprise scale within JPMorgan Chase's ML Center of Excellence. The role involves designing, developing, and maintaining software, engineering data pipelines, feeding data into ML models, and deploying complete systems into production environments with a focus on scalability and reliability.

Lead Applied AI ML role focused on delivering AI/ML solutions, including LLMs and Generative AI, within a financial services enterprise. Requires strong software engineering background in Java/Python and experience with AI/ML techniques.

Lead Software Engineer for AIOps and GenAI solutions within a financial services technology team. Focuses on designing, deploying, and automating AI-driven solutions to enhance system reliability, performance, and incident response. Responsibilities include building RAG pipelines, vector databases, LLM integrations, and agentic workflows, while ensuring regulatory compliance and mentoring engineers on AI adoption.