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About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
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Lead Software Engineer - MLOps / ML Platform joins the Corporate Sector Technology team to build and maintain platform components supporting the end-to-end machine learning model lifecycle, including training, deployment, and monitoring. This role involves designing automated solutions within the SDLC, managing cloud-based infrastructure on AWS using Databricks, EMR, ECS, and S3, and ensuring high-volume, low-latency transactional systems remain stable. The engineer will utilize AI-assisted development tools like GitHub Copilot to improve code quality and delivery speed while adhering to responsible AI practices. Technical requirements include proficiency in Spring Boot, Spring Core, MVC, REST, SOAP, and JMS for microservices development. Additionally, the role requires expertise in SQL, RDBMS schema design, and various AWS services including DynamoDB, EKS, Lambda, and ALB/NLB to solve complex infrastructure challenges within a secure, scalable environment.
Design and maintain platform components for the end-to-end machine learning model lifecycle.
Build and manage cloud infrastructure on AWS including Databricks, EMR, ECS, and S3.
Automate model deployment, testing, and release processes within the MLOps toolchain.
Monitor platform health and resolve performance or stability issues in model serving infrastructure.
Utilize AI-assisted development tools to improve code quality, refactoring, and documentation.
Develop automated solutions for the Platform team to enhance operational efficiency.
Build high-volume, low-latency transactional systems using microservices and Spring Boot.
What we're looking for
Formal training or certification on software engineering concepts and 5+ years of applied experience.
Experience in building high-volume, low-latency, high-throughput transactional systems.
Hands-on server-side development experience with Web Services, XML, SOAP, REST, and JMS.
Experience building microservices using Spring Boot, Spring Core, MVC, Web Services, and Messaging.
Proficiency with AWS services including S3, DynamoDB, ECS, EKS, RDS, Lambda, and ALB/NLB.
Strong knowledge of RDBMS, schema design, SQL, query optimization, indexing, joins, and JDBC.
Experience using enterprise-authorized AI-assisted development tools to evaluate, validate, and refine outputs for security and performance.
Bachelor's degree in a quantitative field with 10+ years experience or Master's degree with 5+ years experience (preferred); AWS certification (preferred).