JPMorgan Lead Software Engineer - Machine Learning 

United States, Georgia, Atlanta 

842042379

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
• Adds to team culture of diversity, equity, inclusion, and respect
• Develop back end features and front end user interfaces which contribute to visualizing the voice of the customer and agent performance
• Contribute to the integration of machine learning models to solve complex business problems and enhance ML-driven applications
• Optimize machine learning models for performance and scalability leveraging cloud based resources
• Demonstrate the ability to continuously learn and stay updated with latest AI and machine learning advancements
• Troubleshoot and debug machine learning related issues
• Initiate and contribute to AI strategy
• Be the technical liaison between business, product, data scientists and engineers

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years of applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language(s)
• Solid experience with Python, SQL, CI/CD pipeline, Github, AWS or Azure or GCP required
• Demonstrated experience with web application development using core Javascript, NodeJS, npm, React.js, React, HTML, SCSS/SASS and CSS
• Understanding of various machine learning algorithms, including supervised and unsupervised learning, neural networks and reinforcement learning
• End-to-end working knowledge on how a machine learning product is built
• Familiarity with MLOPS and components in MLOPS ecosystem
• Good understanding of agile methodologies
• Excellent communication and presentation skills

Preferred qualifications, capabilities, and skills

• In-depth knowledge of the financial services industry and their IT systems
• Practical AWS or Azure cloud native experiences
• Experience with deploying applications using Docker, Kubernetes
• Experience in data streaming tools such as Kafka
• Experience with Generative AI and LLM’s
• Demonstrated experience with modern front-end build pipelines and tool
• Experience in building Single Page Applications using one of the frond end framework(Angular/React/Vue)