JPMorgan Chase
2027 Machine Learning Center of Excellence (NLP) - Summer Associate
$135K–$155K
New York, NY +2 · Full-time · Posted Oct 20, 2026
- Location
- New York, NY
Seattle, WA
Palo Alto, CA - Education
- Currently enrolled in a PhD or MS program in Computer Science, Electrical Engineering, Mathematics, Operations Research, Data Science, or a related quantitative field.
About the job
Conduct an end-to-end research project applying LLM and agentic AI methods to business problems, from data analysis and prototyping through evaluation and presentation.
What you'll do
- Analyze data, engineer features, and develop and evaluate models.
- Build agentic AI prototypes and evaluation frameworks for LLM and agent outputs.
- Collaborate on AI solutions, document and present findings, and help advance work toward production.
What they ask for
- Currently enrolled in a PhD or MS program in a quantitative field, with expected graduation between December 2027 and August 2028.
- Background in at least one of LLMs and agentic AI, NLP, speech recognition, or personalization/recommendation; familiarity with current methods.
- Strong foundations in statistics, probability, and machine learning, including experimental design and metric definition.
- Hands-on experience with modern LLM application patterns; strong Python skills, including deep learning frameworks, Hugging Face, and core data libraries.
Nice to have
- Experience building LLM prototypes with tools, APIs, documents, databases, or search systems; experience with fine-tuning/post-training or LLM evaluation.
- Relevant publications, production-quality coding ability, or familiarity with financial services.
Pay
$135,000.00-$155,000.00 USD base salary (New York, NY); $135,000.00-$155,000.00 USD base salary (Seattle, WA); $135,000.00-$155,000.00 USD base salary (Palo Alto, CA)
Tools
Python, PyTorch, TensorFlow, Hugging Face, NumPy, Pandas, scikit-learn, LangGraph
AI focus
Applies advanced LLM and agentic AI methods to NLP, question answering, speech, reinforcement learning, post-training, and recommendation; builds tool-using workflows and evaluates their quality, reliability, and safety.
Model-written summary · the original posting is authoritative