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.

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: 

• Doctorate (or currently pursuing a doctorate) in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field.
• 3+ years experience delivering, scaling, and maintaining highly successful and innovative machine learning products.

Preferred Qualifications:

• 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.
• Solid Understanding of NLP: In-depth knowledge of natural language processing (NLP) techniques and concepts, including tokenization, semantic analysis, and text generation.
• Have good 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 (TensorFlow, PyTorch, Keras, etc.) will be very helpful.
• Solid algorithm and analytical background and very good understanding on how to apply advanced knowledge to solve real problems.
• Ability to work independently in a team to deliver innovative solutions solving challenging business/technical problems from high level vision and architecture, down to quality design and implementation.
• Experience in parallel or distributed processing, high performance computing, stream computing and SCOPE.
• Self-motivated, self-directed, and be able to work constructively with a wide variety of people, team and changing business priorities.

Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $98,300 - $193,200 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 $127,200 - $208,800 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 

Microsoft will accept applications and processes offers for these roles on an ongoing basis.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

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