채용
Overview
Do you have a keen interest in leveraging cutting-edge AI technologies to solve complex, real-world challenges? Join the Bing Places Data team, where we build innovative solutions to improve search relevance, enhance user experiences, and enable businesses to thrive.
As a Senior Applied Data Scientist, you will
- use Large Language Models (LLMs), Small Language Models (SLMs), and Retrieval-Augmented Generation (RAG) models to create modern, scalable, and efficient systems.
- collaborate with a dynamic, research-driven team that values curiosity, creativity, and a growth mindset.
In this role, you will design and implement advanced AI solutions, staying at the forefront of the latest research in machine learning and natural language processing. You’ll have the opportunity to accelerate your career by working with industry leaders, refining your expertise in applied sciences, and contributing to impactful, customer-centric projects.
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
- Develop and deploy solutions leveraging LLMs, SLMs, and RAG models to solve complex data challenges and enhance the Bing Places platform.
- Stay informed about the latest advancements in AI/ML research, evaluate their applicability, and integrate them into scalable systems.
- Collaborate across multidisciplinary teams, including engineers, data scientists, and product managers, to translate research insights into actionable solutions.
- Create robust pipelines for data processing, training, and inferencing to optimize model performance and scalability.
- Mentor junior team members, foster knowledge sharing, and support recruiting efforts to build a world-class research team.
- Uphold ethical principles in AI, ensuring solutions are fair, unbiased, and aligned with Microsoft’s privacy standards.
Qualifications 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.
Preferred Qualifications:
- Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ 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+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
- 3+ years of experience in publishing peer-reviewed research or presenting at conferences.
- Proven expertise in developing and deploying AI solutions in production environments.
- Experience working with cloud-based infrastructure and big data technologies.
#MicrosoftAI
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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총 지원 클릭 수
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모의 지원자 수
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스크랩
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Microsoft 소개

Microsoft
PublicMicrosoft Corporation is an American multinational technology conglomerate headquartered in Redmond, Washington.
10,001+
직원 수
Redmond
본사 위치
$3000B
기업 가치
리뷰
3.8
5개 리뷰
워라밸
4.1
보상
4.3
문화
3.4
커리어
3.2
경영진
3.0
65%
친구에게 추천
장점
Excellent compensation and benefits package
Four-day workweek with improved work-life balance
Supportive managers and teams
단점
High-pressure environment causing anxiety
Unprofessional interview processes
Limited creative work opportunities
연봉 정보
5,620개 데이터
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Mid/L4 · Applied Science
1개 리포트
$234,166
총 연봉
기본급
$180,128
주식
-
보너스
-
$234,166
$234,166
면접 경험
1개 면접
난이도
4.0
/ 5
소요 기간
14-28주
경험
긍정 0%
보통 0%
부정 100%
면접 과정
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
자주 나오는 질문
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
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