Applied Science PhD Internship

Microsoft

Confirmed live 3 days ago High trust

Quick summary

Work type
On-site
Location
Redmond, WAMountain View, CA
Employment
Intern
Posted
16 days ago
Freshness
Confirmed live 3 days ago
Closes
Feb 22, 2027

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Salary context

How this pay compares to similar roles

Similar $208k
$152k most similar roles pay here $270k

This listing doesn't post a salary. Most similar roles pay $167,650–$249,115.

Based on 240 similar postings.

Employer

About Microsoft

Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing

Microsoft currently has 598 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 586 roles with salary data.

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At a glance

TL;DR · Applied Science PhD Internship

Applied Science: PhD Microsoft AI Internship Opportunities involves analyzing and improving advanced machine learning algorithms and systems at scale to optimize performance across large, complex datasets. You will translate product scenarios into applied ML problems by designing experiments to validate and iterate on solutions for search, ranking, recommendations, retrieval, and language understanding. The role requires building and enhancing data and ML pipelines while utilizing deep learning, reinforcement learning, and probabilistic methods. You will also curate high-quality datasets and apply statistical methods to evaluate model performance. Key technical areas include large-scale distributed systems, content and commerce systems, geospatial intelligence, and research in language models or recommender systems. The position requires a candidate currently pursuing a Doctorate Degree in fields like Computer Science or AI to solve complex problems regarding relevance, discovery, and personalization through state of the art solutions.

What you'll do

  • Analyze and optimize advanced machine learning algorithms and systems at scale across complex datasets.
  • Translate product scenarios and user needs into specific, actionable machine learning problems.
  • Design and execute experiments to validate, iterate, and optimize ML solutions.
  • Develop and scale models for search, ranking, recommendations, retrieval, and language understanding.
  • Prepare, clean, and curate high-quality datasets while identifying data quality issues.
  • Build and enhance data and ML pipelines using statistical methods to validate performance.
  • Communicate technical insights and experimental results clearly to cross-functional stakeholders.
  • Incorporate emerging research and industry trends to improve solution quality and efficiency.

What we're looking for

  • Currently pursuing a Doctorate Degree in Statistics, Econometrics, Computer Science, AI, Electrical/Computer Engineering, or a related field.
  • Must have at least one additional quarter or semester of school remaining after the internship ends.
  • Must be enrolled in a full-time PhD program in a relevant field during the academic term before the internship.
  • A Bachelor's Degree in a relevant field and 2+ years of experience in statistics, predictive analytics, or research.
  • A Master's Degree in Statistics, Econometrics, Computer Science, Electrical/Computer Engineering, or a related field.
  • Experience with search, language models, recommender systems, geospatial intelligence, or content and commerce systems.
  • Experience running controlled experiments and interpreting offline and online evaluation metrics.
  • Familiarity with large-scale distributed systems or productionizing applied science solutions.

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