招聘

Applied Scientist II and Senior Applied Scientist
United States, Washington, Redmond
·
On-site
·
Full-time
·
2w ago
Required Skills
Machine Learning
Overview
Come build community, explore your passions and do your best work at Microsoft. This opportunity will allow you to bring your aspirations, talent, potential - and excitement for the journey ahead.
Monetization at Microsoft AI is at the forefront of one of the fastest growing areas on the Internet—online advertising and intelligent monetization solutions. Our work powers products like Bing Ads, Copilot, and the broader Microsoft ecosystem, serving billions of ad impressions and generating terabytes of user interaction data every day. The rapid evolution of this space presents incredible opportunities and complex technical challenges that require cutting-edge solutions in machine learning, natural language processing, data mining, and large-scale optimization. A PhD is preferred for this role, as it reflects advanced proficiency in scientific methodology, rigorous experimental design, and a strong commitment to reproducible research practices.
We are a world-class organization of passionate scientists and engineers working at the intersection of AI and monetization. Our mission is to select and deliver optimized, personalized content and ads across Microsoft surfaces to maximize a total utility function that balances revenue, user experience, and advertiser value. Whether it's helping users discover what they need, enabling advertisers to reach their ideal audience, or infusing intelligence into Copilot interactions, we are redefining what’s possible in the future of monetization through AI.
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.
Please note, this application is only for roles based in our Redmond, Washington office. For roles in other offices in the United States, please see our Careers site.
- Responsibilities- Building and maintaining production machine learning models for ad retrieval, quality prediction and creative generation.
- Finding insights and forming hypothesis on web-scale data with various machine learning, feature engineering, statistical, and data mining techniques: e.g. regression, classification, NLP, optimization, p-values analysis.
- Designing experiments, understanding the resulting data, and producing actionable, trustworthy conclusions from them.
- Craft and Optimize Prompts for Effective LLM Performance: Design, test, and refine prompts to elicit accurate, relevant, and useful responses from LLMs. This involves understanding the nuances of how the model interprets different inputs, experimenting with various prompt formulations, and iterating based on performance metrics and user feedback.
- Wrangling large amounts of data (think petabytes) using various tools, including open-source ones and your own. All programming languages are welcome, especially Python, R, C#, C++, Java, and SQL.
- Taking complex problems and the associated data and giving the answers in a concise form to assist senior executives in making key business decision.
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.
Preferred 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.
- 2+ years experience delivering, scaling, and maintaining highly successful and innovative machine learning products.
- 1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).
- Experience with Large Language Models: Demonstrated experience working with LLMs, such as GPT, BERT, or similar models, including knowledge of their strengths, limitations, and capabilities.
- Understanding of NLP: In-depth knowledge of natural language processing (NLP) techniques and concepts, including tokenization, semantic analysis, and text generation.
- Understanding of state-of-the-art machine learning and deep learning technologies. In particular, hands-on experiences with deep learning models (DNN, Attention, CNN, RNN) and frameworks (Tensor Flow, Py Torch, Keras, etc.).
- Algorithmic and analytical background and understanding on how to apply advanced knowledge to solve real problems.
- Experience in parallel or distributed processing, high performance computing, stream computing and SCOPE.
Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 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 $131,400 - $215,400 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
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
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
News & Buzz
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AI is a planet-sized bubble — and Microsoft's slump is a taste of the crash to come, tech guru Erik Gordon says - Business Insider
Source: Business Insider
News
·
7w ago