Machine Learning Software Engineer Intern Jobs in Delaware

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Lead Software Engineer at JPMorgan Chase within the Corporate Technology, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job responsibilities

• Design and implement enterprise-grade Machine Learning platforms capable of deploying and running predictive models at scale.
• Develop web applications using service-oriented and microservices architecture with Java and Python frameworks.
• Integrate solutions with AWS Cloud Services, including compute, storage, databases, and security components. 
• Build tools and automation solutions for monitoring, provisioning, and streamlining processes, services, and reporting.
• Establish comprehensive monitoring and alerting frameworks to ensure optimal performance, scalability, availability, and reliability. 
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team. 
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation. 
• Partner closely with Product teams to design, build, and deliver capabilities through agile sprints. 
• Leverage strong operational insights to recommend improvements to upstream products, processes, and policies that enhance the user experience.
• Utilize AI agents and emerging technologies to build prototypes for demonstration purposes, presenting to peer groups, business partners, and senior leadership. 
• Deliver high-quality results within tight deadlines while maintaining a strong focus on code optimization, performance tuning, and engineering best practices.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Experience in building high-volume, low-latency, high-throughput transactional systems.
• Experience in building microservices using Java/Spring Boot and Python/Fastapi/Flask
• Experience with AWS services - S3, DynamoDB, ECS, EKS, RDS, Lambda, and ALB/NLB.
• Experienced with pair programming agents such as GitHub Copilot/Claude code to accelerate prototyping.
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security. 
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices 
• Strong knowledge of RDBMS, schema design, SQL, query optimization, indexing, joins, and JDBC.
• Agile Development experience with SCRUM or similar methodologies
• Completed AWS Developer or Solution Architect Certification
• Excellent problem-solving skills and the ability to think critically and creatively

Preferred qualifications, capabilities, and skills

• Experience in MLOps and building model serving applications
• Experience with artificial intelligence and machine learning tools and framework in development.
• Certification in Databricks
• Experience in observability and production management tools (ex. Splunk / Dynatrace / Grafana)