Applied AI / ML Associate Sr

Role Overview: As a Machine Learning and Python Senior Engineer at JPMorgan Chase within the Asset and Wealth Management Team, you will be a seasoned member of an agile team responsible for designing and delivering trusted market-leading technology products in a secure, stable, and scalable manner. Your role involves carrying out critical technology solutions across multiple technical areas within various business functions to support the firm's objectives. Key Responsibilities: - Develop and deploy AI/ML solutions to drive business value - Design, develop, and deploy state-of-the-art AI/ML/LLM/GenAI solutions aligned with business objectives - Conduct thorough evaluations of Gen AI models, iterate on model architectures, and implement improvements for enhanced performance - Create testing frameworks for models and guide India team developers through the Machine Learning Development Lifecycle (MDLC) - Collaborate with the US Core Client Service AI team to drive AI implementations from India - Work with cross-functional teams to understand requirements and translate them into technical solutions - Stay updated on the latest trends in data science, machine learning, and related fields Qualifications Required: - Formal training or certification in Computer Science, Engineering, or a related field with at least 3 years of applied experience - Proficiency in programming skills, especially in Python - Hands-on experience in applied AI/ML engineering, leading developers, and working in a fast-paced environment - Proficient in programming languages like Python for model development, experimentation, and integration with Azure OpenAI API - Strong collaboration and communication skills to work effectively with cross-functional teams - Problem-solving and analytical skills with attention to detail - Experience with cloud platforms for deploying and scaling AI/ML models Additional Details: - Preferred qualifications include experience in backend development, knowledge of SRE practices, and exposure to cloud automation technologies - Familiarity with large language models (LLMs), databases, programming languages, web frameworks, APIs, and microservices is beneficial - Ability to assess and choose suitable LLM tools and models for tasks, curate custom datasets, fine-tune LLM models, and design advanced LLM prompts - Execute experiments to push the capability limits of LLM models and enhance their dependability,