Join our 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. We offer unparalleled opportunities for career growth and a collaborative environment where you can thrive and contribute to meaningful projects.

As an Applied AI ML Senior Associate within the Corporate Oversight and Governance Technology team, you will solve challenging and impactful problems across a wide range of Corporate functions. You will study complex business problems and apply advanced algorithms to develop, test, and evaluate AI/ML applications or models. Working with the firm's rich data pool using Python/Spark via AWS, you will derive business insights and present them to non-technical audiences, contributing to stronger business programs and improved efficiency.

• Proactively develop understanding of key business problems and processes.
• Execute tasks throughout a 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, ensuring high-quality outputs in summarization and text generation.
• Conduct thorough evaluations of generative models (e.g., GPT-4), iterate on model architectures, and implement improvements to enhance overall performance in NLP applications.
• Implement monitoring mechanisms to track model performance in real-time and ensure model reliability.
• Communicate AI/ML/LLM/GenAI capabilities and results to both technical and non-technical audiences.
• Generate structured and meaningful insights from data analysis and modeling exercises and present them in an appropriate format according to the audience.
• Collaborate with other data scientists and machine learning engineers to deploy machine learning solutions.
• Carry out ad-hoc and periodic analysis as required by the business stakeholder, model risk function, and other groups.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Minimum 5 years of demonstrated experience in applied AI/ML, with a track record of developing and deploying business-critical machine learning models in production.
• Proficiency in programming languages like Python for model development, experimentation, and integration with OpenAI API.
• Experience with machine learning frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit-learn, and OpenAI API.
• Experience in building AI/ML models on structured and unstructured data along with model explainability and model monitoring.
• Solid understanding of fundamentals of statistics, machine learning (e.g., classification, regression, time series, deep learning, reinforcement learning), and generative model architectures, particularly GANs, VAEs.
• Experience with a broad range of analytical toolkits, such as SQL, Spark, Scikit-Learn, and XGBoost.
• Experience with graph analytics and neural networks (PyTorch).
• Excellent problem-solving, communication (verbal and written), and teamwork skills.

• Expertise in building AI/ML models on structured and unstructured data along with model explainability and model monitoring.
• Expertise in designing and implementing pipelines using Retrieval-Augmented Generation (RAG).
• Familiarity with the financial services industry.