Senior Applied Scientist-Ads Monetization

Microsoft Monetization is building the next generation of AI-powered advertising and commerce experiences across Search Audience Shopping Copilot and emerging agentic surfaces.

As conversational agents increasingly become the interface between users and businesses we are reimagining how products services and ads are discovered selected personalized and delivered.

In this role you will

• Design and implement cutting-edge machine learning models and algorithms that power advertising systems across Microsoft Ads Bing Copilot and beyond.
• Work on large-scale machine learning challenges spanning user understanding ad representation retrieval recommendation ranking and optimization with the goal of maximizing value for both users and advertiser
• Apply and advance technologies in natural language processing (NLP) computer vision (CV) large language models (LLMs) Generative AI and Agentic AI.
• Have a direct impact on millions of users and advertisers by delivering robust and scalable solutions that improve advertising experiences and business outcomes.

This role is part of Microsoft AI Experiences - Monetization team and is responsible for solving end-to-end machine learning and optimization problems across our ads products.

Microsofts 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.

AI Experiences employees who live within a 50- mile commute of a designated Microsoft Hub in the U.S. 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.

• Defining the ad relevance problem across different ad scenarios to optimize both the user and advertiser experience.
• Driving algorithmic and modeling improvements to the system using primarily deep learning techniques from NLP and computer vision including the latest LLM models.
• Deploying robust and scalable solutions to continuously improve ad relevance.
• Analyzing model and system performance to identify opportunities based on offline and online testing.

Required Qualifications:

• Bachelors 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 Masters 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.

Preferred Qualifications:

• Masters Degree in Statistics Econometrics Computer Science Electrical 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 of experience developing natural language processing or multimodal machine learning systems using deep learning including hands-on experience with transformer-based small language models (SLMs) or large language models (LLMs).
  • OR 4 years working experience in Computer Vision (CV) with latest deep learning technologies including Vision Transformers.
• 4 years of experience developing and operating production machine learning or AI systems using Python C or equivalent programming languages.
• Experience in online advertising.
• Experience with distributed training or inference for SLMs and LLMs including data and model parallelism mixed-precision training checkpointing experiment management performance optimization and efficient serving.
• 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 evaluating SLMs LLMs or agentic systems using task-specific offline metrics human or model-assisted evaluation safety and robustness testing latency and cost analysis and controlled online experiments.
• Experience designing and implementing agentic AI systems that use tool calling retrieval planning memory structured outputs multi-step workflows or multi-agent coordination with appropriate safeguards and observability.
• Experience applying responsible AI practices to model and agent development including evaluation for safety reliability privacy security bias groundedness and misuse risks.
• Have publications at peer-reviewed Data Science/AI conferences (- Knowledge Discovery and Data MiningCIKM- Conference on Information and Knowledge ManagementSIGIR- Special Interest Group on Information RetrievalNeurIPS- Neural Information Processing SystemsCVPR- Computer Vision and Pattern RecognitionICMLInternational Conference on Machine LearningICLR- International Conference on Learning RepresentationsICCV- International Conference on Computer Vision andACL- Association for Computational Linguistics).

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Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119800 - $234700 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 $160200 - $261000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
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.

Required Experience:

IC