Machine Learning Center of Excellence (NLP) Summer Associate

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 such as retrieval-augmented generation, fine-tuning, and agent harness design.
• Develop evaluation frameworks to measure the quality, reliability, and safety of LLM and agent outputs.
• Translate business problems into AI solutions and move them toward production environments.
• Document methodology, assumptions, and results to ensure work is reproducible.
• Present findings and key learnings to both technical and business audiences.

What we're looking for

• Currently enrolled in a PhD or MS program in a quantitative field with an expected graduation date between December 2027 and August 2028.
• Solid background in LLMs, agentic AI, NLP, speech recognition, or personalization/recommendation with familiarity with state-of-the-art methods.
• Strong foundation in statistics, probability, and machine learning to design experiments and define metrics.
• Hands-on exposure to LLM application patterns like prompting, embeddings, RAG, tool calling, and agentic workflows.
• Strong Python skills including PyTorch or TensorFlow, Hugging Face, NumPy, Pandas, and scikit-learn.
• Clear written and spoken communication skills for technical and business audiences.
• Experience building LLM prototypes using frameworks like LangGraph, LangChain, LlamaIndex, or Semantic Kernel (preferred).
• Experience with fine-tuning, post-training, or published research in major AI conferences (preferred).