We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a AI/ML Lead Engineer at JPMorgan Chase within Asset and Wealth Management, you will have the opportunity to work on state-of-the-art Language Modelling projects that will transform the operating model for the Wealth Management business. The key focus areas within this position will be on prompt engineering for Large Language Models (LLMs), and supporting the development and deployment of prompt-based models for various NLP tasks such as text classification, question answering, and language generation on a rich universe of financial and market data including unique datasets which can be leveraged to define the experiences for our clients and employees across the globe. At JPMorgan, you will be part of a world-class analytics community dedicated to skill development and career growth in analytics, data science, machine learning and beyond.
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
- 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
- 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
- Programming skills in Python with experience in PyTorch or TensorFlow
- Thorough knowledge of deep learning concepts, including attention mechanisms, transformers, and language modelling
- Experience in data pre-processing, feature engineering, and data analysis
- Excellent problem-solving and the ability to communicate ideas and results to stakeholders and leadership in a clear and concise manner
- Ability to work in a fast-paced environment on multiple projects simultaneously
- Basic knowledge of deployment processes, including experience with GIT and version control systems for efficient collaboration and code management in MLOps projects
- Familiarity with data structures and algorithms, enabling effective problem-solving and optimization in machine learning workflows
- Hands on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environment
Preferred qualifications, capabilities, and skills
- PhD in Computer Science, Data Science or related field
- Experience in developing and deploying production-grade NLP models in the financial services industry
- Knowledge of financial products and services including trading, investment and risk management
- Familiarity with machine learning frameworks like scikit-learn and Keras
- Experience in developing APIs and integrating NLP models into software applications
