Join our team as a Machine Learning Software Engineer and play a pivotal role in shaping the future of Machine Learning and AI solutions within the Consumer & Community Banking sector at JPMorgan Chase.

As a Machine Learning Software Engineer at JPMorgan Chase within the Consumer & Community Banking, Operations 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 Adds to team culture of diversity, equity, inclusion, and respect Develop and implement machine learing models to solve complex buiness problems and enhance ML-driven applications    Optimize machine learning models for performance and scalability leveraging cloud based resources Demonstrate self-promote and ability to continuosly 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 Be a part of our innovation and transformation roadmap 

 

Required qualifications, capabilities, and skills

      •   Formal training or certification on software engineering concepts and 3+ 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
      •   Proven track record in developing machine learning models at scale from inception to business impact on a cloud platform
      •   Strong understanding of various machine learning algorithms, including supervised and unsupervised learning, neural networks and reinforcement learning
      •   Hands-on experience in optimizing LLM prompts
      •   Strong 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 experience
•   Experience in data streaming tools such as Kafka
•   Experience with Generative AI and LLM’s