Lead Software Engineer

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

As the Lead Python Engineer at JPMorgan Chase within the One Chase Experience Platform team in Consumer Banking, you will have the opportunity to design, develop, and deploy AI/ML solutions that enhance customer experiences and promote innovation across our digital banking products. You will collaborate with data scientists, product managers, and platform engineers to deliver scalable, production-grade machine learning applications.

Job Responsibilities

• Develop, test, and deploy AI/ML models and solutions using Python and related frameworks.
• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
• Build and maintain data pipelines for model training, validation, and deployment.
• Optimize and refactor existing code for performance, scalability, and maintainability.
• Integrate AI/ML models into the One Chase Experience Platform, ensuring seamless customer experiences.
• Monitor, troubleshoot, and improve deployed models and services.
• Document technical designs, processes, and best practices.

• Formal training or certification on software engineering concepts and 5+ years applied experience
• 3+ years of professional experience in Python development, with a focus on AI/ML applications.
• Strong knowledge of machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with data processing libraries (e.g., pandas, NumPy) and building data pipelines.
• Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and containerization (e.g., Docker, Kubernetes).
• Experience deploying and maintaining machine learning models in production environments.
• Solid understanding of software engineering best practices, including version control (Git), testing, and CI/CD.
• Excellent problem-solving and communication skills.

• Experience in the financial services or consumer banking sector.
• Knowledge of MLOps tools and practices.
• Familiarity with RESTful APIs and microservices architecture.
• Experience working in Agile development environments.