Lead Software Engineer - Machine Learning Engineer

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer - Machine Learning Engineer at JPMorgan Chase within the Consumer and Community Banking, Operations Technology team, 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. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems


• Develops secure high-quality production code, and reviews and debugs code written by others


• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems


• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture


• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies


• Adds to team culture of diversity, equity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience


• Hands-on practical experience delivering system design, application development, testing, and operational stability


• Advanced experience in Python and distributed computing frameworks such as PySpark


• Experience in setting up Machine Learning platform infrastructure and deploying to the cloud to develop and train machine learning models


• Hands-on experience and solid understanding of machine learning methods and MLOps, deploying and scaling ML and AI Models on Public cloud services


• Hands-on experience with AWS cloud-based application development and infrastructure - EC2, EKS


• Experience in designing and building AWS data pipelines using Lambda, SQS, SNS, Athena, Glue, EMR, S3 to facilitate ML training


• Analyzing and evaluating the ongoing performance of developed models


• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages


• Hands-on practical experience in system design, application development, testing, and operational stability

• Modern and emerging technologies