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Applied Scientist 2

Microsoft

Applied Scientist 2

Microsoft

China, Beijing, Beijing; China, Jiangsu, Suzhou

·

On-site

·

Full-time

·

1w ago

Overview

Microsoft AI Organization aims to the best user experience for Web Search, Advertisement, Cloud, and Enterprise services. The Search Experience Group in Microsoft AI has more than 400 scientists and engineers, working on various NLP/Multi-modal techniques and applications.

We're looking for passionate and experienced engineers and scientists to help us on our mission of employing deep learning to understand all the data on the web - the largest store of information in human history. With this understanding we power end-user experiences across a variety of NLP/Multi-modal related areas, especially

  • RAG System.
  • Generative answers.
  • Build up the world-class AI systems with novel NLP techniques and engineering excellence.
  • Explore cutting-edge AI technology and deliver both research and production impact.

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- Drive core technologies and E2E production delivery by leveraging State-of-Art AI technologies.
  • Address challenges in products through Deep Learning and Reinforcement Learning approaches and transfer novel ideas to production applications.
  • Development of deep learning models for Microsoft AI scenarios, including generative search and answers, knowledge experience, et al.
  • Pushing the envelope on deep learning by:Defining problems and establishing metrics
  • Gathering training data at scale
  • Exploring model design and architecture
  • Exploring learning objectives and tasks

Qualifications:

Required Qualifications:

  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ 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 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
  • OR equivalent experience.
  • Experiences in applying deep learning, advanced AI solution, RAG techniques and drive E2E AI product development.
  • Minimum 2 years of experience in NLP/search related areas.
  • Passionate and self-motivated.
  • Good communication skills, both verbal and written.

Preferred Qualifications:

  • Bachelor'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 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.
  • Good experience in advanced AI solution post-train, finetuning.
  • Experience in RAG system.
  • Solid problem-solving skills, and ability to work independently.

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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About Microsoft

Microsoft

A software corporation that develops, manufactures, licenses, supports, and sells a range of software products and services.

10,001+

Employees

Redmond

Headquarters

$3000B

Valuation

Reviews

3.8

5 reviews

Work Life Balance

4.1

Compensation

4.3

Culture

3.4

Career

3.2

Management

3.0

65%

Recommend to a Friend

Pros

Excellent compensation and benefits package

Four-day workweek with improved work-life balance

Supportive managers and teams

Cons

High-pressure environment causing anxiety

Unprofessional interview processes

Limited creative work opportunities

Salary Ranges

5,571 data points

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Mid/L4 · Data and Applied Scientist

0 reports

$202,099

total / year

Base

$149,342

Stock

$32,252

Bonus

$20,505

$139,572

$301,212

Interview Experience

7 interviews

Difficulty

3.7

/ 5

Duration

14-28 weeks

Offer Rate

14%

Experience

Positive 14%

Neutral 29%

Negative 57%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Technical Interview

5

Onsite/Virtual Interviews

6

Final Round

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience