Job Description

Shape the future of customer-facing financial experiences by leading applied artificial intelligence and machine learning solutions that deliver real business impact. Join a team that values engineering excellence, modern architecture, and strong collaboration across product, data, and risk partners. Bring your expertise to a role with broad mobility, meaningful technical ownership, and opportunities to influence platform standards and adoption.

As an Applied AI ML Lead at JPMorgan Chase within the Consumer and Community Banking - Architecture and Engineering team, you are an integral part of a team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for delivering critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

In this role, you will partner closely with product, engineering, data, and control stakeholders to identify high-value machine learning use cases and take them from concept to production. You will balance delivery speed with security, resiliency, and responsible use expectations, ensuring solutions are scalable and supportable. You will also help teams adopt repeatable patterns for model development, deployment, and monitoring. Success requires strong technical judgment, clear communication, and the ability to lead through influence in a fast-moving environment.

Job Responsibilities

Design end-to-end software and machine learning solutions that are secure, resilient, and scalable for production use.
Develop high-quality production code in Python and perform thorough code reviews to improve correctness, security, and maintainability.
Build and operationalize machine learning models, including generative approaches where applicable, from experimentation through deployment and ongoing support.
Define evaluation, testing, and monitoring practices for model and application performance, reliability, and drift to sustain production outcomes.
Automate recurring remediation and operational tasks to improve stability, reduce incidents, and streamline support.
Lead technical solutioning across multiple components and services, aligning architecture decisions with business requirements and platform constraints.
Drive workflow automation opportunities using machine learning to improve customer or employee experiences while maintaining appropriate controls.
Evaluate external vendors, startups, and internal solutions by probing architecture, technical fit, and integration feasibility within existing systems.
Mentor engineers through communities of practice and day-to-day guidance, reinforcing an inclusive, respectful, and high-performing team culture.

Required qualifications, capabilities, and skills

Formal training or certification in software engineering concepts and 5+ years of applied software engineering experience.
Hands-on experience delivering system design, application development, testing, and production support for customer- or business-critical systems.
Professional experience developing in Python, including building and supporting machine learning workloads.
Experience implementing automation and continuous delivery practices in a production engineering environment.
Working knowledge of the full software development life cycle, including design, build, test, release, and operate.
Experience building or integrating machine learning solutions, including generative model use cases in production or pre-production environments.
Experience working with cloud-native technologies and deploying workloads to a public cloud environment (for example, Amazon Web Services).
Experience working in financial services technology or similarly regulated environments with security and control expectations.

Preferred qualifications, capabilities, and skills

Experience designing or implementing agent-based artificial intelligence solutions (for example, tool-using or multi-step reasoning workflows).
Experience fine-tuning or adapting language models, including small language models and large reasoning models, for domain-specific use cases.
Familiarity with model evaluation techniques for generative solutions (for example, automated quality checks and human-in-the-loop review patterns).
Experience partnering with governance, risk, or control stakeholders on responsible model deployment and ongoing monitoring.

About Us

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

About the Team

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

Applied AI ML - India Lead

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