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求人Microsoft

Senior Applied Scientist

Microsoft

Senior Applied Scientist

Microsoft

India, Telangana, Hyderabad; India, Karnataka, Bangalore

·

On-site

·

Full-time

·

2w ago

Overview

The Crowd Intelligence Platform (CIP) team, part of the MAI platform organization, is building an AI‑driven testing platform that ensures high quality for Microsoft AI products such as Bing, Copilot, MSN, and Edge—both pre‑release and in production. The platform leverages Agentic AI to perform scalable, intelligent testing across diverse product surfaces.

We are looking for a Senior Applied Scientist to help design, build, and scale AI‑powered testing systems that can be applied generically across a wide range of cutting‑edge MAI products. This role offers a unique opportunity to apply AI at scale to real‑world product quality challenges and directly influence how MAI products are tested and improved.

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.

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50-mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

  • Responsibilities- Build and scale AI‑driven testing capabilities using LLMs, prompts, and agent‑based workflows to validate MAI products across scenarios, geographies, and product surfaces.
  • Design and optimize prompts, models, and agent behaviors to perform functional, quality, and experience‑focused testing at scale.
  • Collaborate closely with product and engineering teams across MAI and beyond to understand testing needs and translate them into efficient, AI‑powered testing workflows.
  • Develop metrics and evaluation frameworks to measure test quality, coverage, effectiveness, and signal accuracy across AI‑driven testing pipelines.
  • Create actionable outputs and insights (issues, summaries, trends, and recommendations) that product owners can directly consume to fix defects and improve product quality.
  • Continuously evolve the platform toward more autonomous and agentic workflows, reducing manual effort while increasing depth and reliability of testing.
  • Partner with engineers and platform teams to operationalize data science solutions in production, ensuring scalability, reliability, and performance.

Qualifications:

Required Qualifications:

  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 7+ 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 5+ years related experience (e.g., statistics, predictive analytics, research).
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ year(s) related experience (e.g., statistics, predictive analytics, research).
  • OR equivalent experience.
  • 4+ years of solid experience in Data Science, Applied AI, or Machine Learning, with a track record of building solutions that operate at scale.
  • Hands‑on experience with LLMs, prompt engineering, and/or agentic AI systems.
  • Solid foundation in statistics, experimentation, and metrics design, especially for evaluating AI system quality.
  • Experience working with data pipelines, model evaluation, and production systems.
  • Ability to work across multiple product teams, influence without authority, and translate ambiguous testing needs into concrete AI solutions.
  • Solid communication skills to explain complex AI outputs clearly to engineering and product stakeholders.

Preferred Qualifications:

  • 3+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
  • 3+ year(s) experience developing and deploying live production systems, as part of a product team.
  • 3+ year(s) experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.

#MicrosoftAI

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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Microsoftについて

Microsoft

Microsoft

Public

Microsoft Corporation is an American multinational technology conglomerate headquartered in Redmond, Washington.

10,001+

従業員数

Redmond

本社所在地

$3000B

企業価値

レビュー

3.8

5件のレビュー

ワークライフバランス

4.1

報酬

4.3

企業文化

3.4

キャリア

3.2

経営陣

3.0

65%

友人に勧める

良い点

Excellent compensation and benefits package

Four-day workweek with improved work-life balance

Supportive managers and teams

改善点

High-pressure environment causing anxiety

Unprofessional interview processes

Limited creative work opportunities

給与レンジ

5,620件のデータ

Senior/L5

Senior/L5 · Account Management

5件のレポート

$209,483

年収総額

基本給

$181,941

ストック

-

ボーナス

-

$194,895

$209,483

面接体験

7件の面接

難易度

3.7

/ 5

期間

14-28週間

内定率

14%

体験

ポジティブ 14%

普通 29%

ネガティブ 57%

面接プロセス

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Technical Interview

5

Onsite/Virtual Interviews

6

Final Round

7

Offer

よくある質問

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience