We have an exciting and rewarding opportunity for you to take your AI/ML career to the next level. Join us to make a significant impact on risk technology solutions at JPMorgan Chase.
Job summary
As an Applied AI/ML Software Engineer III at JPMorgan Chase within the Risk Technology team, you research, develop, and implement innovative Generative AI solutions that transform our risk assessment capabilities. You turn cutting-edge AI research into practical applications that enhance operational efficiencies and integrate with our risk calculation frameworks, supporting the firm's business objectives.
Job responsibilities
- Execute research and experimentation with Large Language Models and Generative AI technologies to solve complex risk technology challenges
- Create secure and high-quality prototypes and proof-of-concepts for AI applications in risk management
- Produce scalable and production-ready AI systems that integrate with existing risk calculation frameworks
- Gather, analyze, and synthesize insights from diverse data sets to improve AI model performance and risk assessment capabilities
- Proactively identify opportunities for AI implementation and recommend optimal solutions for specific use cases
- Contribute to AI/ML communities of practice and events that explore new and emerging technologies
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience with focus on AI/ML applications
- Hands-on practical experience with Large Language Models (e.g., GPT, BERT)
- Strong understanding of Generative AI concepts and applications
- Proficient in Python programming and experience with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face)
- Familiarity with cloud-based AI services such as AWS, Azure, or GCP
- Overall knowledge of the Software Development Life Cycle and software engineering best practices including Git, CI/CD, and testing
- Strong communication skills to explain complex technical concepts
Preferred qualifications, capabilities, and skills
- Knowledge of model fine-tuning and Retrieval Augmented Generation
- Understanding of risk management principles in financial services
- Experience with large-scale database technologies
- Familiarity with agile development methodologies
