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JPMorgan Lead Software Engineer - Machine Learning 
United States, Georgia, Atlanta 
842042379

08.09.2024

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)