Senior Applied Scientist - Ads Monetization

Microsoft • Redmond, WA

18h • $119,800 - $261,000 • Hybrid

About The Position

Microsoft Monetization is building AI-powered advertising and commerce experiences across Search, Audience, Shopping, Copilot, and emerging agentic surfaces. As conversational agents become an interface between users and businesses, the team is reimagining how products, services, and ads are discovered, selected, personalized, and delivered.

This role is part of the Microsoft AI Experiences Monetization team and focuses on end-to-end machine learning and optimization problems across advertising products. The Senior Applied Scientist will develop models and algorithms for advertising systems, addressing large-scale challenges in user understanding, ad representation, retrieval, recommendation, ranking, and optimization. The work applies technologies including NLP, computer vision, large language models, generative AI, and agentic AI to improve relevance and outcomes for users and advertisers.

The role is expected to deliver robust, scalable solutions with impact across Microsoft Ads, Bing, Copilot, and other surfaces. AI Experiences employees living within a 50-mile commute of a designated U.S. Microsoft Hub are expected to work from the office at least four days per week, subject to local law and jurisdictional variation.

Requirements

• Bachelor's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field, and 4+ years of related experience; or a master's degree in one of these fields and 3+ years of related experience; or a doctorate in one of these fields and 1+ year of related experience; 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 SLMs or LLMs, or 4+ years of work experience in computer vision using current 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.
• Ability to work independently within a team to deliver innovative solutions to challenging business and technical problems, from high-level vision and architecture through design and implementation.

Nice To Haves

• Master's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field and 6+ years of related experience; or doctorate in one of these fields and 3+ years of related experience; or equivalent experience.
• 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.
• 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 using 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.
• Publications at peer-reviewed Data Science or AI conferences, such as KDD, CIKM, SIGIR, NeurIPS, CVPR, ICML, ICLR, ICCV, or ACL.

Responsibilities

• Define the ad relevance problem across different ad scenarios to optimize user and advertiser experiences.
• Drive algorithmic and modeling improvements, primarily using deep learning techniques from NLP and computer vision, including the latest LLM models.
• Deploy robust and scalable solutions to continuously improve ad relevance.
• Analyze model and system performance to identify opportunities through offline and online testing.
• Design and implement machine learning models and algorithms for advertising systems across Microsoft Ads, Bing, Copilot, and other surfaces.
• Address large-scale machine learning challenges involving user understanding, ad representation, retrieval, recommendation, ranking, and optimization.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior