Applied AI ML Associate

You thrive on diversity and creativity, and JPMorgan Chase welcomes individuals who share the vision of making a lasting impact. Your unique combination of design thinking and experience will help achieve new heights. As an Applied AI ML Associate at JPMorgan Chase within the Asset & Wealth Management, you are part of an agile team that enhances, designs, and delivers data collection, storage, access, and analytics solutions securely, stably, and at scale. As an emerging member of a data engineering team, your role involves executing data solutions through designing, developing, and technically troubleshooting multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role. - Supports, develops, and implements GenAI and Agentic AI solutions using Python to enhance automation and decision-making processes. - Develops and maintains machine learning models to solve complex business problems. Collaborates with cross-functional teams to identify opportunities for leveraging data to drive business solutions. - Analyses large, heterogeneous datasets to extract actionable insights and inform decision-making. Stays updated with the latest advancements in machine learning, especially Large Language Models and agentic systems. Communicates findings and recommendations through clear and concise reports and presentations. - Updates logical or physical data models based on new use cases with minimal supervision. - Adds to team culture of diversity, opportunity, inclusion, and respect. Required qualifications, capabilities, and skills: - Formal training or certification in applied AI/ML concepts and 3+ years of applied experience. - Proficiency in Python and SQL and familiarity with good software engineering practices. - Strong experience in developing, testing machine learning solutions using frameworks such as TensorFlow, PyTorch, or scikit-learn. - Solid intuitive grasp of fundamental concepts from probability, statistics, linear algebra, and calculus. - Experience deploying on AWS cloud infrastructure using Lambda, Glue, S3, etc. - Experience in deep neural networks and familiarity with the latest developments in related fields. - Experience in LLM model finetuning and continuous learning techniques. - Experience in prompt engineering techniques and state-of-the-art LLM architectures.,