Applied AI ML Associate Senior - PAG

Role Overview: You have an exciting opportunity to advance your Applied AI engineering career as an Applied AI ML Associate Sr at JPMorgan Chase within the Consumer and Community Banking - Wealth Management. In this role, you will be part of an agile team responsible for designing and delivering market-leading technology products in a secure, stable, and scalable manner. Your key responsibility will be to implement critical technology solutions across multiple technical domains to support various business functions in achieving the firm's objectives. Key Responsibilities: - Execute software solutions, design, development, and technical troubleshooting with a focus on innovative approaches to building solutions and solving technical problems. - Create secure and high-quality production code that integrates seamlessly with generative AI systems and other technologies. - Produce architecture and design artifacts for complex generative AI applications, ensuring adherence to design constraints through software code development. - Analyze and synthesize data from diverse data sets to enhance generative AI applications and systems. - Proactively identify hidden problems and patterns in data to drive improvements in coding hygiene and system architecture specific to generative AI. - Contribute to software engineering communities of practice and explore emerging generative AI technologies. Qualification Required: - Formal training or certification in software engineering concepts with at least 3 years of applied experience. - Proficiency in coding in languages like Python and AI/ML frameworks. - Experience in developing, debugging, and maintaining code in a corporate environment using modern programming languages and database querying languages. - Comprehensive knowledge of the Software Development Life Cycle, particularly focused on generative AI applications. - Understanding of agile methodologies such as CI/CD, Application Resiliency, and Security in the context of AI/ML. - Knowledge of software applications and technical processes in disciplines like cloud computing, artificial intelligence, machine learning, and mobile technologies. - Expertise in AWS, GenAI/ML technologies, Agentic AI Development, SLM's, LRM's, and Model Finetuning. Additional Details: - Experience with AI model optimization and performance tuning for efficient and scalable AI solutions is preferred. - Familiarity with data engineering practices to support AI model training and deployment. - Ability to collaborate with cross-functional teams to integrate generative AI solutions into broader business processes and applications. - Strong understanding of machine learning algorithms, including supervised, unsupervised, and reinforcement learning. - Experience with AI/ML libraries and tools such as TensorFlow, PyTorch, Scikit-learn, and Keras.,