Applied AI/ML Lead

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Data Scientist Lead at JPMorgan Chase within the Asset and Wealth Management, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

• Design, deploy and manage prompt-based models on LLMs for various NLP tasks in the financial services domain


• Conduct research on prompt engineering techniques to improve the performance of prompt-based models within the financial services field, exploring and utilizing LLM orchestration and agentic AI libraries.


• Collaborate with cross-functional teams to identify requirements and develop solutions to meet business needs within the organization


• Communicate effectively with both technical and non-technical stakeholders


• Build and maintain data pipelines and data processing workflows for prompt engineering on LLMs utilizing cloud services for scalability and efficiency.


• Develop and maintain tools and framework for prompt-based model training, evaluation and optimization


• Analyze and interpret data to evaluate model performance to identify areas of improvement

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience


• Experience with prompt design and implementation or chatbot application


• Strong programming skills in Python with experience in PyTorch or TensorFlow


• Experience building data pipelines for both structured and unstructured data processing.


• Experience in developing APIs and integrating NLP or LLM models into software applications


• Hands-on experience with cloud platforms (AWS or Azure) for AI/ML deployment and data processing.


• Excellent problem-solving and the ability to communicate ideas and results to stakeholders and leadership in a clear and concise manner


• Basic knowledge of deployment processes, including experience with GIT and version control systems


• Familiarity with LLM orchestration and agentic AI libraries


• Hands on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environment

•  Familiarity with model fine-tuning techniques such as DPO and RLHF.


• Knowledge of Java, Spark


•  Knowledge of financial products and services including trading, investment and risk management