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Senior Applied Scientist

Microsoft

Senior Applied Scientist

Microsoft

China, Beijing, Beijing

·

On-site

·

Full-time

·

3w ago

Required Skills

Machine Learning

LLMs

Prompt Engineering

RAG

Python

Debugging

Overview

We are seeking a highly skilled and motivated Applied Scientist with strong hands-on experience in building and optimizing agentic AI systems. Our mission is to benefit Office users with rich content and tool support to raise productivity, and we are building the AI and engineering system to make it happen. This position offers an exciting opportunity to design and develop highly complex and comprehensive systems combining engineering, AI and human participation. You will work closely with product managers, designers, and users to turn ideas and AI into reality and make a great impact to all global Office users.

  • Responsibilities- Design and implement advanced LLM-based architectures and agentic systems for real-world product scenarios.

  • Translate research breakthroughs into production-ready algorithms, contributing to core capabilities such as reasoning, planning, long-term memory, code-gen based design.

  • Monitor and improve model performance post-deployment through data-driven iteration and error analysis.

  • Collaborate across teams to deliver robust, scalable models aligned with product objectives and user value.

  • Contribute to the organization’s scientific direction by identifying research opportunities that drive long-term differentiation.

  • Qualifications- M.S. or Ph.D. in Computer Science, Machine Learning, or a related field, or equivalent practical experience.

  • 5+ years of experience in applied machine learning, with a focus on LLMs, agent systems, or reinforcement learning.

  • Strong hands-on experience with prompt engineering, context engineering, retrieval-augmented generation (RAG), tool use, planning agents, and long-context modeling, etc.

  • Familiarity with model training pipelines using Py Torch, Tensor Flow, JAX, or similar frameworks, evaluation strategies, and model deployment best practices.

  • Strong coding and debugging skills, and comfort working in cross-functional, agile environments.

  • Experience on office document generation and related applications is a plus.

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