Applied Science: Microsoft AI Internship Opportunities - Redmond

Microsoft Microsoft · Big Tech · Redmond, WA +1 · Applied Sciences

This internship focuses on applying AI/ML expertise to real-world product scenarios within Microsoft's AI Content and Commerce, Search Fundamentals, and Search Place teams. Interns will work on problems in search, personalization, NLP, computer vision, and recommendation systems, translating research into production-ready solutions for products like Copilot.

What you'd actually do

  1. Analyze and improve advanced machine learning algorithms and systems at scale, optimizing performance across large, complex datasets.
  2. Translate product scenarios and user needs into applied ML problems; design and execute experiments to validate, iterate, and optimize solutions.
  3. Develop and scale models for search, ranking, recommendations, retrieval, and language understanding using modern AI techniques (e.g., deep learning, reinforcement learning, probabilistic methods).
  4. Prepare, clean, and curate high-quality datasets—identifying data quality issues, defining inclusion criteria, and enabling robust feature development.
  5. Build and enhance data and ML pipelines (data collection, preparation, modeling), applying statistical methods to validate assumptions and evaluate model performance.

Skills

Required

  • Statistics
  • Econometrics
  • Computer Science
  • Artificial Intelligence
  • Electrical or Computer Engineering
  • supervised and unsupervised learning
  • deep learning
  • transformers
  • sequence modeling
  • reinforcement learning
  • advanced data science techniques
  • statistical analysis
  • hypothesis testing
  • large datasets
  • deploying robust data pipelines

Nice to have

  • Master's Degree
  • research publications
  • coursework or project experience relevant to search, language models, recommender systems, geospatial or location intelligence, or content and commerce systems
  • controlled experiments
  • offline and online evaluation metrics
  • large-scale distributed systems
  • productionizing applied science solutions

What the JD emphasized

  • Must have at least one additional quarter/semester of school remaining following the completion of the internship.
  • Candidate must be enrolled in a full time PhD program in area relevant for the role during the academic term immediately before their internship.

Other signals

  • applying expertise in supervised and unsupervised learning, deep learning (especially transformers and sequence modeling), reinforcement learning
  • translate complex business challenges—spanning search, personalization, natural language processing, computer vision, and recommendation systems—into practical, impactful solutions
  • drive research into production
  • shape the future of Copilot and intelligent content