About the role#
As a Summer Associate within the Machine Learning Center of Excellence (MLCOE), you will apply advanced LLM and agentic AI methods to complex business problems. You will own a research project from start to finish, working alongside mentors, business experts, and engineers. This role provides hands-on experience in areas such as natural language processing, speech recognition, and recommendation systems. Your work will contribute to financial products, productivity tools, and risk management efforts.
What you'll do#
- Perform exploratory data analysis, feature engineering, model development, and evaluation using structured and unstructured datasets.
- Design and build prototypes of agentic AI systems, including multi-step workflows that use tools and reason across tasks.
- Apply and experiment with LLM techniques like retrieval-augmented generation, tool and function calling, fine-tuning, and agent harness design.
- Develop evaluation frameworks to measure the quality, reliability, and safety of LLM and agent outputs.
- Collaborate with mentors and stakeholders to turn business problems into AI solutions and help move them toward production.
- Document methodology, assumptions, and results to ensure work is reproducible.
- Present findings and key learnings to technical and business audiences.
What you'll need#
- Current enrollment in a PhD or MS program in Computer Science, Electrical Engineering, Mathematics, Operations Research, Data Science, or a related quantitative field.
- Expected graduation date between December 2027 and August 2028.
- Solid background in at least one of: large language models, agentic AI, natural language processing, speech recognition, or personalization/recommendation.
- Strong foundation in statistics, probability, and machine learning, with the ability to design experiments and define metrics.
- Hands-on exposure to LLM application patterns like prompting, embeddings, retrieval-augmented generation, tool calling, and multi-step workflows.
- Strong Python skills, including experience with PyTorch or TensorFlow, the Hugging Face ecosystem, and core libraries like NumPy, Pandas, and scikit-learn.
- Clear communication skills for both technical and business audiences.
- Experience building LLM-powered prototypes connecting models to tools, APIs, or databases using frameworks like LangGraph, LangChain, LlamaIndex, or Semantic Kernel is preferred.
- Experience with fine-tuning, post-training, or building evaluation frameworks is a plus.
- Published research in a major conference or journal and the ability to write production-quality code are valued.
- Familiarity with the financial services industry is helpful.
Location & details#
- Location: New York, New York, United States.
- Term: Summer 2027.
- Modality: Hybrid.
- Employment: Full-time.
- Compensation: Paid internship.
About JPMorganChase
JPMorganChase is a financial services firm based in New York City. It operates in 100 markets and serves millions of customers, including corporate, institutional, and government clients. The company manages assets and investments while providing banking solutions and business advice. It traces its history to 1799 and was established in its current form in 2000. The firm employs over 235,000 people.
How to get in at JPMorganChase
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