Develop cutting-edge large-scale Personalization, Search, Natural Language Processing and Conversational AI Systems to serve customers and internal agents supporting the bank’s operations.
Requirements
- PhD in Computer Science, with a strong research and industry work experience in AI/ML, Distributed Computing, ML Ops, Recommender Systems, NLU and Information Retrieval.
- Hands-on extensive experience in developing large-scale machine learning solutions based on big data to solve real world problems (e.g. Classification, Regression, or Recommender Systems).
- Advanced demonstratable programming skills of 10-15 years (PhD plus industry experience) on more than 1 programming language is required. Preferred: Spark, Python, Scala, Java.
- Strong background in data structures, algorithms, operating systems, compilers, distributed computing and databases.
- PhD in computer science with concentration in AI/ML.
- Full understanding and advanced programming skills using distributed infrastructure, platforms, and computational methods (including distributed ML).
Responsibilities
- Develop Foundational Models for Personalization, Search and Conversational AI using Chase enterprise data.
- Build ML Frameworks and Libraries to enable scalable approaches for training and inference of ML models
- Utilize large-scale distributed computing to effectively apply Agentic-AI in real-world applications to serve JPMC customers and service agents across channels.
- Use and extend GenAI capabilities to build differentiating applications that are customized to suit product and customer requirements.
- Effectively and efficiently develop various evaluation mechanisms to identify, address and improve the results of LLM based systems.
- Build and Lead a team of Machine Learning applied researchers and engineers.
- Contribute to the full product development lifecycle, including defining the objective and key product deliverables.
Other
- Outstanding written and oral communication skills to present analytical findings and exercise influence among key project stakeholders.
- Provide technical and career guidance to the team members.
- Collaborate with cross-functional partners including product, data and engineering.
- Lead by example to provide the best service and build the most appropriate applications in a timely fashion to address customer concerns, resolving critical issues, and push forward on future roadmap and priorities.
