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Senior Applied Scientist

Microsoft
$119,800.00 - $234,700.00 / yr
United States, Washington, Redmond
Feb 14, 2026
Overview

Microsoft Cloud Operations and Innovation (CO+I) underpins Microsoft's global cloud infrastructure, driving the innovation, planning, design, construction, and operation of one of the largest data center fleets in the world. We are seeking an exceptional Senior Applied Scientist to join the Data Center Applied AI team. In this role, you will play a pivotal role in advancing and integrating cuttingedge, multimodal agentic AI systems into core tools and operational workflows that power Microsoft's data centers. Your work will drive operational efficiency at scale and help advance Microsoft's mission to empower every person and every organization on the planet to achieve more through intelligent, multimodal AI agents.

As a Senior Applied Scientist, you willbridge stateoftheart AI research with productiongrade engineering, delivering agent architectures that are reliable, secure, scalable, observable, and measurable. You will collaborate closely with Business and Engineering to build and deploy agentic capabilities across workflow automation, information retrieval, retrievalaugmented generation (RAG), tool and function calling, longhorizon task execution, and multiagent orchestration.

This role blends deep AI and applied science expertise with strong engineering judgment, operational rigor, and a bias for action. Success requires endtoend ownership, a growth mindset, and strong customer empathy. Join us to shape the future of agentic AI for data center operations at global 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.



Responsibilities
  • Advance Applied AI Research to Improve Quality and Reliability
    • Apply deep expertise in Generative AI, deep learning, NLP, and multimodal models to translate cutting-edge research into high-impact, production-ready AI solutions.
    • Design and execute experiments that measurably improve agent planning, memory, grounding, reasoning, and longhorizon task completion.
    • Perform lightweight finetuning (e.g., LoRA and related techniques) on multimodal and large multimodal language models-to improve entity recognition, reasoning accuracy, and response quality.
    • Implement stateoftheart approaches using foundation models, advanced prompt engineering, RAG, knowledge graphs, and multiagent architectures, complemented by classical ML techniques where appropriate.
  • Build and Ship Scalable Agentic AI Systems
    • Architect and implement endtoend agent workflows that decompose user intent into executable plans, intelligently select and invoke tools, and recover gracefully from errors and edge cases.
    • Rapidly prototype solutions and partner with engineering teams to drive production deployment, including debugging live systems and building AIOps workflows.
    • Use data and telemetry to identify AI quality gaps, generate insights, and deliver proofs of concept that apply research innovations to realworld operational challenges.
    • Design robust multistep reasoning and tooluse strategies, including function calling, code execution, APIs, and secure connectors, with strong safety and reliability guardrails.
    • Drive production excellence across latency, reliability, cost efficiency, observability, monitoring, and safe fallback behaviors.
  • Own Evaluation, Metrics, and Iteration Loops
    • Define tasklevel evaluation metrics for agentic behavior, including success rate, toolcall accuracy, step efficiency, hallucination rate, safety violations, timetocompletion, and user satisfaction.
    • Build and maintain offline and online evaluation pipelines, including:
      • Golden datasets, scenario simulators, and regression test suites
      • Humanintheloop evaluation frameworks and rubric design
      • A/B experimentation and telemetrydriven iteration loops
  • Collaborate Across Disciplines and Lead Technical Execution
    • Partner with business and engineering stakeholders to translate requirements into clear technical specifications, research plans, and delivery milestones.
    • Lead design reviews and influence engineering decisions across agent frameworks, model integration, and system architecture.
    • Mentor and support other applied scientists and engineers, raising the bar for applied AI execution and production quality
  • Other
  • Embody ourCultureandValues


Qualifications

Required/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.

Preferred Qualifications

  • Experience with Azure technology Stack
  • Experience with parameterefficient finetuning techniques (e.g., LoRA) for LLMs or multimodal models.
  • Handson experience building agentic or toolaugmented LLM systems, including function calling, planners, and API/tool integration.
  • Experience with advanced RAG architectures, such as hybrid retrieval, reranking, grounding, and citation strategies.
  • Strong AIOps depth, including quality drift detection, alerting, rollback, and telemetrydriven optimization.
  • Experience optimizing systems for latency, reliability, scalability, and cost efficiency at enterprise scale.
  • Prior experience working on missioncritical or largescale enterprise AI systems.
  • Demonstrated mentorship or technical leadership within applied science or engineering teams.

Background Check 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.

#COICareers

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 $158,400 - $258,000 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-pay

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.

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