Applied Science: PhD Microsoft AI Internship Opportunities

MicrosoftMicrosoftMountain View, California, United States | Redmond, Washington, United States
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Posted

8/26/2026

Employment

Intern

Range

$7k - $15k/month

Work style

Hybrid

4 days in office

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AI summary

Core responsibilities

Analyze and improve advanced machine learning algorithms and systems at scale while translating product scenarios into applied ML solutions. Collaborate cross-functionally to design experiments, build data pipelines, and deliver integrated solutions for search, ranking, and recommendation systems.

Requirements overview

Candidates must be currently pursuing a Doctorate degree in a relevant field such as Computer Science, Statistics, or AI with at least one academic term remaining. Preferred qualifications include prior research experience, familiarity with large-scale distributed systems, and proficiency in modern AI techniques.

Key skills

Machine learningDeep learningTransformersSequence modelingReinforcement learningData scienceStatistical analysisHypothesis testingNatural language processingComputer visionRecommendation systemsAzureData pipelinesPythonDistributed systemsPredictive analytics

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Education requirements

postgraduate degree

About Microsoft

Industry

Software Development

Employees

232,851

Type

Public Company

Size

10,001+ employees

Every company has a mission. What's ours? To empower every person and every organization to achieve more. We believe technology can and should be a force for good and that meaningful innovation contributes to a brighter world in the future and today. Our culture doesn’t just encourage curiosity; it embraces it. Each day we make progress together by showing up as our authentic selves. We show up with a learn-it-all mentality. We show up cheering on others, knowing their success doesn't diminish our own. We show up every day open to learning our own biases, changing our behavior, and inviting in differences. Because impact matters. Microsoft operates in 190 countries and is made up of approximately 228,000 passionate employees worldwide.

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Job categories

TechnologyScience & ResearchSoftwareData & AnalyticsEngineering

Description

Overview Bring your passion for innovation and research to a team at the forefront of artificial intelligence and machine learning. If you’re eager to make significant contributions across user engagement, intelligent experiences, and real product scenarios, this opportunity within Microsoft AI Content, Commerce, & Monetization (CCM), Search Fundamentals, Search Experiences, or Search Places will excite you. As an Applied Scientist PhD Intern, you will apply your expertise in areas such as supervised and unsupervised learning, deep learning (especially transformers and sequence modeling), reinforcement learning for optimizing user outcomes, and advanced data science techniques. You’ll translate complex business challenges—spanning search, personalization, natural language processing, computer vision, and recommendation systems—into practical, impactful solutions using Azure and other cloud-based technologies. Your experience with statistical analysis, hypothesis testing, large datasets, and deploying robust data pipelines will be valued as you drive research into production. This role allows you to shape the future of Copilot and intelligent content, influencing Microsoft's direction as you directly support our overarching mission and vision. At Microsoft, our mission to empower every person and every organization on the planet to achieve more guides how we partner with customers to deliver trusted, impactful solutions. With a growth‑mindset culture, we innovate responsibly and measure success by shared progress, people, teams, and customers. Join us to do meaningful work that changes the world and helps shape what’s next for everyone. Responsibilities Analyze and improve advanced machine learning algorithms and systems at scale, optimizing performance across large, complex datasets. Translate product scenarios and user needs into applied ML problems; design and execute experiments to validate, iterate, and optimize solutions. Develop and scale models for search, ranking, recommendations, retrieval, and language understanding using modern AI techniques (e.g., deep learning, reinforcement learning, probabilistic methods). Prepare, clean, and curate high-quality datasets—identifying data quality issues, defining inclusion criteria, and enabling robust feature development. Build and enhance data and ML pipelines (data collection, preparation, modeling), applying statistical methods to validate assumptions and evaluate model performance. Collaborate cross-functionally with scientists, engineers, and product stakeholders to iterate on ideas and deliver real-world, product-integrated solutions. Communicate technical insights and experimental results clearly, while continuously incorporating emerging research, tools, and industry trends to improve solution quality and efficiency. Qualifications Required Qualifications Currently pursuing a Doctorate Degree in Statistics, Econometrics, Computer Science, Artificial Intelligence, Electrical or Computer Engineering, or related field. 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. Preferred Qualifications Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research) Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field Equivalent experience. Explore product challenges using state of the art solutions. Research publications, coursework, or project experience relevant to search, language models, recommender systems, geospatial or location 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. Passion for building AI experiences that improve relevance, discovery, personalization, and end-user satisfaction. The base pay range for this internship is USD $6,810.00 - $13,480.00 per month. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $8,920.00 - $14,610.00 per month. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-intern-pay Microsoft accepts applications and processes offers for these roles on an ongoing basis throughout the academic calendar (September - April) This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Requirements

  • Machine learning
  • Deep learning
  • Transformers
  • Sequence modeling
  • Reinforcement learning
  • Data science
  • Statistical analysis
  • Hypothesis testing
  • Natural language processing
  • Computer vision
  • Recommendation systems
  • Azure
  • Data pipelines
  • Python
  • Distributed systems
  • Predictive analytics

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