MNC InsiderMNC Insider
Microsoft logo

Senior Applied Scientist

Microsoft

Senior Applied Scientist

full-timePosted: Aug 24, 2026Updated: Aug 27, 2026Redmond, WA, US

Job Description

OverviewThe AI Platform and Tools team in the Windows Platform and Developer organization builds end-to-end systems for AI inference and agent workflows on Windows. Our work makes Windows a versatile and powerful platform for on-device AI, enabling compelling experiences for customers and providing developers with the tools they need to build the next generation of intelligent applications. We also work on technologies that move work seamlessly between on-device and cloud-hosted models so experiences can deliver the right balance of quality, latency, privacy, reliability, and cost.We are looking for a Senior Applied Scientist to develop and ship machine learning innovations across the Windows AI stack. In this role, you will research, prototype, evaluate, and productionize techniques that improve model quality and the efficiency of AI workloads on a diverse range of Windows devices. You will work at the intersection of applied machine learning and systems, partnering with software engineers, hardware architects, program managers, and researchers to solve challenges in model optimization, search and retrieval, inference orchestration, and agent execution.This is an opportunity to turn advances in generative AI, ML/algorithms for search and retrieval, and agentic systems into platform capabilities used by developers and customers at Windows scale.Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees, we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day, we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.ResponsibilitiesBringing the State of the Art to ProductsPartners with Engineering and Product teams to turn advances in generative AI, search and retrieval, agentic systems, and efficient inference into measurable product impact. Builds prototypes and production-ready platform components for inference, retrieval, and agent workflows across heterogeneous CPUs, GPUs, and NPUs on Windows devices.Leveraging Applied ResearchDevelops and evaluates data-, research-, and experimentation-backed techniques for on-device and hybrid inference, including quantization, distillation, model adaptation, compression, indexing, embeddings, and hardware-aware optimization. Investigates intelligent model and workload placement across device and cloud resources while balancing quality, latency, memory, power, reliability, privacy, and cost.Machine Learning Functionality, Insights, and Technical ToolsDesigns datasets, metrics, experiments, and benchmarks for model and system evaluation; analyzes behavior to identify quality and performance bottlenecks and drives improvements across the AI workload lifecycle. Implements and integrates machine learning components, runtimes, developer APIs, and tools, then validates their behavior through production-oriented testing and monitoring on representative hardware and workloads.DocumentationDocuments scientific approaches, experiment plans, datasets, evaluation results, design decisions, and implementation guidance so that work can be reproduced, reviewed, and adopted by partner teams. Communicates findings through design reviews, technical presentations, and, where appropriate, patents or publications.Ethics and PrivacyApplies Responsible AI and Microsoft security principles when selecting data, designing experiments, and developing on-device, hybrid, retrieval, and agent systems. Identifies risks involving privacy, security, bias, and reliability and incorporates appropriate safeguards into technical solutions.Capability Management and NetworkingMentors engineers and product partners on applied machine learning, evaluation, inference optimization, search and retrieval, and agent workflows. Builds collaborative relationships across science, engineering, hardware, and product teams; contributes to technical planning and helps teams apply research methods and best practices to platform problems.QualificationsRequired/Minimum Qualifications:Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research).OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research).OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research).OR equivalent experience.Other Requirements: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter. Preferred Qualifications:Master's Degree in Statistics, Mathematics, Physics, Computer Science, Electrical or Computer Engineering, or a related field AND 6+ years of related experience.OR Doctorate in one of these fields AND 2+ years of related experience.OR equivalent experience.2+ years of experience developing and deploying production machine learning systems.Experience with generative AI, language or multimodal models, agentic systems, model post-training, RAG/Search, Approximate Nearest Neighbor algorithms and ML frameworks. #W+DJOBS Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. 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 $160,200 - $261,000 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:https://careers.microsoft.com/us/en/us-corporate-payThis 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.

Locations

  • Redmond, WA, US
  • Mountain View, CA, US

Salary

119,800 - 234,700 USD / yearly

Skills Required

  • generative AIintermediate

Required Qualifications

  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research).OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research).OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research).OR equivalent experience. (experience, 4 years)
  • Other Requirements: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: (experience)
  • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter. (experience)

Preferred Qualifications

  • Master's Degree in Statistics, Mathematics, Physics, Computer Science, Electrical or Computer Engineering, or a related field AND 6+ years of related experience.OR Doctorate in one of these fields AND 2+ years of related experience.OR equivalent experience. (experience, 6 years)
  • 2+ years of experience developing and deploying production machine learning systems. (experience, 2 years)
  • Experience with generative AI, language or multimodal models, agentic systems, model post-training, RAG/Search, Approximate Nearest Neighbor algorithms and ML frameworks. (experience)
  • Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. 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 $160,200 - $261,000 per year. (experience)
  • Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:https://careers.microsoft.com/us/en/us-corporate-pay (experience)
  • This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. (experience)

Responsibilities

  • Bringing the State of the Art to Products
  • Partners with Engineering and Product teams to turn advances in generative AI, search and retrieval, agentic systems, and efficient inference into measurable product impact. Builds prototypes and production-ready platform components for inference, retrieval, and agent workflows across heterogeneous CPUs, GPUs, and NPUs on Windows devices.
  • Leveraging Applied Research
  • Develops and evaluates data-, research-, and experimentation-backed techniques for on-device and hybrid inference, including quantization, distillation, model adaptation, compression, indexing, embeddings, and hardware-aware optimization. Investigates intelligent model and workload placement across device and cloud resources while balancing quality, latency, memory, power, reliability, privacy, and cost.
  • Machine Learning Functionality, Insights, and Technical Tools
  • Designs datasets, metrics, experiments, and benchmarks for model and system evaluation; analyzes behavior to identify quality and performance bottlenecks and drives improvements across the AI workload lifecycle. Implements and integrates machine learning components, runtimes, developer APIs, and tools, then validates their behavior through production-oriented testing and monitoring on representative hardware and workloads.
  • Documents scientific approaches, experiment plans, datasets, evaluation results, design decisions, and implementation guidance so that work can be reproduced, reviewed, and adopted by partner teams. Communicates findings through design reviews, technical presentations, and, where appropriate, patents or publications.
  • Ethics and Privacy
  • Applies Responsible AI and Microsoft security principles when selecting data, designing experiments, and developing on-device, hybrid, retrieval, and agent systems. Identifies risks involving privacy, security, bias, and reliability and incorporates appropriate safeguards into technical solutions.
  • Capability Management and Networking
  • Mentors engineers and product partners on applied machine learning, evaluation, inference optimization, search and retrieval, and agent workflows. Builds collaborative relationships across science, engineering, hardware, and product teams; contributes to technical planning and helps teams apply research methods and best practices to platform problems.

Benefits

  • general: Flexibility: Balance what matters—your work, your life, and your team—through trust, autonomy, and shared accountability
  • general: Growth: Stretch your skills, expand your impact, and grow with support that meets you where you are
  • general: Wellbeing: Support for your body, mind, and financial future—so you can stay energized and do your best work
  • general: Community PCS: Find your people, build your network, and feel supported every step of the way

Travel Requirements

Less than 25%

Target Your Resume for "Senior Applied Scientist" , Microsoft

Get personalized recommendations to optimize your resume specifically for Senior Applied Scientist. Takes only 15 seconds!

AI-powered keyword optimization
Skills matching & gap analysis
Experience alignment suggestions

Check Your ATS Score for "Senior Applied Scientist" , Microsoft

Find out how well your resume matches this job's requirements. Get comprehensive analysis including ATS compatibility, keyword matching, skill gaps, and personalized recommendations.

ATS compatibility check
Keyword optimization analysis
Skill matching & gap identification
Format & readability score

Tags & Categories

Applied SciencesResearch, Applied, & Data SciencesApplied SciencesResearch, Applied, & Data Sciences

Answer 10 quick questions to check your fit for Senior Applied Scientist @ Microsoft.

Quiz Challenge
10 Questions
~2 Minutes
Instant Score

Related Books and Jobs

No related jobs found at the moment.