Applied AI ML Associate

Role Overview: Join the fast-paced Corporate Oversight and Governance Technology AI/ML team at J.P. Morgan, where your skills and passion will drive innovation and make a significant impact. You will have unparalleled opportunities for career growth in a collaborative environment where you can thrive and contribute to meaningful projects. As an Applied AI ML Associate within the team, you will solve challenging and impactful problems across various Corporate functions by studying complex business problems and applying advanced algorithms to develop, test, and evaluate AI/ML applications or models using Python/Spark via AWS. Key Responsibilities: - Proactively develop an understanding of key business problems and processes. - Execute tasks throughout the model development process, including data wrangling/analysis, model training, testing, and selection. - Implement optimization strategies to fine-tune generative models for specific NLP use cases. - Conduct thorough evaluations of generative models and iterate on model architectures for enhanced performance in NLP applications. - Implement monitoring mechanisms to track model performance in real-time and ensure reliability. - Communicate AI/ML capabilities and results to both technical and non-technical audiences. - Generate structured insights from data analysis and modeling exercises and present them appropriately. - Collaborate with other data scientists and machine learning engineers to deploy machine learning solutions. - Carry out ad-hoc and periodic analysis as required by business stakeholders. Qualifications Required: - Formal training or certification in applied AI/ML concepts and 2+ years of applied experience. - Proficiency in Python for model development, experimentation, and integration with OpenAI API. - Experience with machine learning frameworks like TensorFlow, PyTorch, Scikit-learn, and OpenAI API. - Solid understanding of statistics, machine learning, and generative model architectures. - Experience with analytical toolkits such as SQL, Spark, Scikit-Learn, and XGBoost. - Experience with graph analytics and neural networks (PyTorch). - Excellent problem-solving, communication, and teamwork skills. Note: No additional details about the company were provided in the job description.,