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Microsoft
Microsoft

Empowering every person and organization on the planet to achieve more.

Senior Applied Scientist

RoleData Science
LevelSenior
LocationRedmond, WA, United States
WorkOn-site
TypeFull-time
Posted2 months ago
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Required skills

Machine Learning

Overview:

We’re hiring a Senior Applied Scientist with expertise in natural language processing (NLP), deep learning, and Ads recommender systems in Redmond, WA or Mountain View, CA.

In this role, you will design and implement cutting-edge machine learning models and algorithms that power relevance systems across all surfaces for Microsoft Ads and Shopping including Bing, Copilot, and beyond.

You will have a direct impact on millions of users and advertisers, delivering scalable solutions to enhance ad relevance and optimize user experiences. This role is part of Microsoft Artificial Intelligence (MAI)-Ads Engineering and is responsible for the end-to-end relevance problem for our ads and shopping products.

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- Own high‑impact and open-ended relevance problem areas across Product Ads and Shopping including providing strategic direction to solve problems and applying deep subject matter knowledge to support business impact.
  • Drive algorithmic and modeling improvements to the system using primarily deep learning techniques from NLP and computer vision, including latest LLM models, to deliver clear and measurable product impact
  • Exercise solid technical judgment on metrics, evaluation strategies, and tradeoffs optimizing for overall product ROI rather than isolated metrics.
  • Act as a technical leader and mentor, providing design reviews and documenting to share modeling guidance and evaluation best practices for other applied scientists to promote innovation.
  • Collaborate deeply across disciplines (Engineering, PM, Research, Data Science), translating scientific intent into production‑ready systems and constraints.
  • Operate with high independence and accountability, anticipating risks, planning for unknowns, and requiring minimal oversight to deliver sustained impact at scale.
  • Use your deep understanding of fairness and bias to contribute to ethics and privacy policies related to research processes and data collection.

Qualifications:

Required Qualifications:

  • Bachelor's Degree in Data Science, Machine Learning, Statistics, Computer Science or Computer Engineering or related field AND 4+ years related experience (e.g., statistics predictive analytics, research)OR Master's Degree in Data Science, Machine Learning, Statistics, Computer Science or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Data Science, Machine Learning, Statistics, Computer Science or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
  • OR equivalent experience.

Preferred Qualifications:

  • Data Science, Machine Learning, Statistics, Computer Science 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.
  • 4+ years working experience in statistical natural language processing (NLP) with the latest deep learning technologies including transformer and LLMs OR 4+ years working experience in Computer Vision (CV) with latest deep learning technologies including Vision Transformers.
  • 4+ years working experience with coding in production systems using C++, C#, Java or Python.

#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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About Microsoft

Microsoft

Microsoft

Public

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

10,001+

Employees

Redmond

Headquarters

$3000B

Valuation

Reviews

10 reviews

4.4

10 reviews

Work-life balance

3.2

Compensation

4.1

Culture

4.3

Career

3.8

Management

4.0

82%

Recommend to a friend

Pros

Cutting-edge technology and innovative projects

Great team culture and collaborative atmosphere

Excellent benefits and competitive compensation

Cons

Heavy workload and frequent overtime

High expectations and stressful environment

Bureaucratic processes can be slow

Salary Ranges

5,620 data points

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Mid/L4 · Applied Science

1 reports

$234,166

total per year

Base

$180,128

Stock

-

Bonus

-

$234,166

$234,166

Interview experience

1 interviews

Difficulty

4.0

/ 5

Duration

14-28 weeks

Experience

Positive 0%

Neutral 0%

Negative 100%

Interview process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

Common questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge