JPMorgan Chase within the Commercial & Investment Bank's Global Banking team is looking to leverage AI innovation to support its business operations.
Requirements
- Expert in at least one of the following areas: Large Language Models, Natural Language Processing, Knowledge Graph, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis.
- Good understanding of Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics.
- Must have good knowledge on agentic patterns and relevant frameworks, such as LangChain, LangGraph, Auto-GPT etc.
- Strong understanding of AI implementation in software development and legacy code transformation.
- Experience in advanced applied ML areas such as GPU optimization, finetuning, embedding models, inferencing, prompt engineering, AI evaluation, RAG (Similarity Search).
- Demonstrated expertise in machine learning frameworks: Tensorflow, Pytorch, pyG, Keras, MXNet, Scikit-Learn.
- Strong programming knowledge of python, spark; Strong grasp on vector operations using numpy, scipy; Strong grasp on distributed computation using Multithreading, Multi GPUs, Dask, Ray, Polars etc.
Responsibilities
- Lead a local AI/ML team with accountability and engagement into a global organization.
- Deliver AI/ML projects through our ML development life cycle using Agile methodology.
- Help transform business requirements into AI/ML specifications, define milestones, and ensure timely delivery.
- Design experiments, establish mathematical intuitions, implement algorithms, execute test cases, validate results and productionize highly performant, scalable, trustworthy and often explainable solution.
- Participate and contribute back to firmwide Machine Learning communities through patenting, publications and speaking engagements.
- Evaluate and design effective processes and systems to facilitate communication, improve execution, and ensure accountability.
- Exercise sound technical judgment, anticipate bottlenecks, escalate effectively, and balance business needs versus technical constraints.
Other
- Deep knowledge of AI/ML and effective leadership to inspire the team, align cross-functional stakeholders, engage senior leadership, and drive business results.
- Mentor and guide team members, fostering an inclusive culture with a growth mindset.
- Collaborate on setting the technical vision and executing strategic roadmaps to drive AI innovation.
- Work with product and business teams to define goals and roadmaps. Maintain alignment with cross-functional stakeholders.
- Mentor junior team members delivering successful projects and building successful career in the firm.
