Applied Scientist II | Microsoft Careers

Microsoft

Hybrid

Quick summary

Work type
Hybrid
Location
Salary
$102,100–$202,200 / yr
Posted
today
Closes
Dec 12, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $181k
This role $152k
$86k most similar roles pay here $251k

This role pays less than 76% of similar roles. Most pay $155,000–$207,350 — the shaded band above. At the midpoint, this role pays about $152k versus about $181k for comparable roles.

Based on 238 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 1580 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 1408 roles with salary data.

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At a glance

TL;DR · Applied Scientist II | Microsoft Careers

The Applied Scientist II role within Microsoft's Core Search and AI team focuses on advancing next-generation search technologies using large language models at scale. This position involves developing deep expertise in areas such as retrieval, ranking, and relevance systems to enhance user experiences by integrating LLM-powered capabilities. Day-to-day responsibilities include conducting advanced research, identifying product opportunities through trend analysis, and translating findings into scalable production improvements. The ideal candidate will have a background in machine learning, preferably with experience in Python or C++, and should be adept at building large-scale ML systems for search and recommendation engines. This role requires a strong understanding of AI technologies and the ability to drive measurable business impact by refining RAG pipelines and monitoring model performance using quantitative metrics.

What you'll do

  • Develop deep knowledge of a service or domain to identify product opportunities and share emerging trends.
  • Explore data types needed for complex problem-solving, applying expertise to drive measurable business impact.
  • Build and optimize retrieval, ranking, and relevance systems that integrate with large language model experiences.
  • Refine RAG pipelines to enhance retrieval fidelity, reduce hallucinations, and deliver context-aware responses.
  • Translate research into production by running experiments, analyzing results, and collaborating with engineering teams.

What we're looking for

  • Master's degree in a relevant field (CS, EE) with 1+ year of experience or equivalent.
  • Doctorate in a relevant field.
  • Experience applying machine learning techniques in industry.
  • Proficiency in Python, C++, C#, C, or Java.
  • Background in Machine Learning, LLMs, and NLP research.
  • Ability to build and improve large-scale ML systems for search and recommendation.

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