Applied Sciences INTERN

We are seeking an Applied Sciences INTERN to join our team in Multiple Locations, IL.

Responsibilities

• Formulate and investigate applied research questions in large language models, agentic AI, and machine learning for real-world spreadsheet scenarios.
• Design and implement experiments, prototypes, and model or agent improvements, including prompt optimization, fine-tuning, post-training, retrieval, and tool-use approaches.
• Build and curate representative datasets, benchmarks, and evaluation methods that measure task quality, reliability, latency, and efficiency.
• Analyze model and agent behavior using quantitative metrics and qualitative error analysis; identify failure modes and translate findings into actionable improvements.
• Collaborate with applied scientists, engineers, and product partners to integrate promising research ideas into Microsoft 365 Copilot in Excel experiences.
• Communicate methods, results, limitations, and recommendations clearly through technical documents, presentations, and peer reviews.

Qualifications

• You are pursuing your doctoral research under the supervision of an advisor who is actively conducting research in LLMs domain, generative AI, or closely related fields.
• You have at least one full year of study remaining before completing your degree and are available to dedicate a minimum of 2 full days per week to the internship.
• Full proficiency in Python and common machine learning and deep learning frameworks such as PyTorch, TensorFlow, or equivalent tools.
• Good familiarity with using coding agents like Claude code and GitHub copilot.

Preferred Qualifications

• Publications at recognized conferences or journals in the LLMs domain are highly valued, particularly work involving post-training, model adaptation, agentic AI, or evaluation.
• Demonstrated knowledge and experience in designing rigorous experiments, curating high-quality datasets, developing benchmarks and graders, and applying statistical methods to evaluate and analyze model quality and behavior.
• Strong written and verbal communication skills and the ability to collaborate effectively in a multidisciplinary, globally distributed team.
• Previous professional experience in software engineering is considered an advantage.