Bring your expertise in applied artificial intelligence and machine learning to a team improving how Markets Operations runs at scale. You will partner across operations, product, engineering, and data to deliver production-grade solutions with measurable impact. In a collaborative environment, you will shape strategy, mentor talent, and build durable capabilities designed for reliability, control, and real-world adoption.

As an Applied Artificial Intelligence and Machine Learning Lead at JPMorganChase within Markets Operations in the Commercial & Investment Bank, you will drive the strategy, design, and delivery of solutions that improve operational efficiency, resilience, and control outcomes. You will lead a team of scientists and engineers and collaborate with senior stakeholders to prioritize high-impact opportunities and deliver solutions that scale. You will set technical direction, strengthen engineering and governance practices, and translate complex concepts into clear, outcome-focused results.

Job Responsibilities:

• Lead the end-to-end delivery of machine learning and generative AI solutions that measurably improve Markets Operations outcomes

• Set technical direction and execution strategy across model development, deployment, and adoption aligned to business priorities

• Oversee the architecture and production deployment of AI applications, including agent-based and workflow-automation solutions

• Manage, coach, and develop a team of scientists and engineers, fostering a collaborative and inclusive culture of continuous learning

• Establish and enforce best practices for model monitoring, evaluation, and performance optimization in production environments

• Partner with business, operations, and technology leaders to shape problem statements, success metrics, and delivery roadmaps

• Guide analysis of large, complex datasets to identify drivers, risks, and automation opportunities

• Ensure solutions are engineered for reliability, scalability, and maintainability, with strong operational readiness

• Communicate technical approaches, decisions, and results through clear documentation and cross-functional forums

Required Qualifications, Capabilities, and Skills:

• Formal training or certification on applied artificial intelligence and machine learning concepts and 5+ years applied experience
• Bachelor’s or Master’s degree in computer science, data science, artificial intelligence, or a related field (or equivalent experience)
• Demonstrated leadership delivering AI/ML initiatives from concept through production, including team and stakeholder management
• Strong applied experience in machine learning, including feature engineering, model development, and statistical analysis on large datasets
• Hands-on proficiency in Python and common machine learning libraries (for example, scikit-learn, TensorFlow, or PyTorch)
• Proven experience deploying, operating, and maintaining production machine learning systems, including incident and performance ownership
• Working knowledge of machine learning operations practices (machine learning lifecycle management, automation, and reproducibility)
• Experience building and deploying generative AI applications and evaluating large language model outputs for quality and risk
• Strong communication skills, including the ability to translate technical concepts for senior stakeholders and non-technical partners

Preferred Qualifications, Capabilities, and Skills:

• Doctorate in a quantitative field or equivalent advanced applied research experience
• Experience delivering AI/ML solutions in financial services, capital markets, or operations-focused environments
• Experience working in highly regulated environments with strong model risk, governance, or control expectations
• Experience designing scalable system architectures for AI products and platforms across multiple stakeholder groups

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