Applied Sciences Intern

Microsoft Microsoft · Big Tech · IL · Applied Sciences

This is an applied research internship focused on large language models and agentic AI within the context of Microsoft 365 Copilot for Excel. The intern will investigate research questions, design and implement experiments, build datasets and evaluation methods, analyze model behavior, and collaborate on integrating research into product experiences. The role requires a PhD student with remaining study time, proficiency in Python and ML frameworks, and experience with coding agents. Preferred qualifications include publications in LLMs, experience with post-training, agentic AI, evaluation, and dataset curation.

What you'd actually do

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

Skills

Required

  • Python
  • PyTorch
  • TensorFlow
  • LLMs
  • generative AI

Nice to have

  • prompt optimization
  • fine-tuning
  • post-training
  • retrieval
  • tool-use
  • datasets
  • benchmarks
  • evaluation methods
  • model behavior analysis
  • quantitative metrics
  • qualitative error analysis
  • technical documents
  • presentations
  • peer reviews
  • Claude code
  • GitHub copilot
  • model adaptation
  • agentic AI
  • statistical methods
  • written communication
  • verbal communication
  • collaboration
  • software engineering

What the JD emphasized

  • doctoral research
  • minimum of 2 full days per week
  • Publications at recognized conferences or journals in the LLMs domain are highly valued
  • 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

Other signals

  • LLMs
  • agentic AI
  • machine learning
  • Excel experiences