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YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_f863c53d-b02"},"title":"Principal Applied Scientist","description":"<p>We are seeking a Principal Applied Scientist to lead the next generation of click-through-rate (CTR) for Microsoft Advertising. This is a high-impact role responsible for advancing large-scale ranking models that power Microsoft Advertising, generating billions of impressions and revenue-critical decisions daily.</p>\n<p>You will combine deep machine learning expertise, solid engineering execution, and business intuition to modernize our prediction stack, drive model innovation, and mentor a growing team of scientists and engineers. This role is ideal for someone who thrives in complex, high-scale systems, who brings thought leadership to ML strategy, and who raises the bar for engineering rigor, curiosity, and business-driven decision making across the team.</p>\n<p>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.</p>\n<p>Responsibilities:</p>\n<p>ML / Modeling Leadership</p>\n<ul>\n<li>Lead the end-to-end development of large-scale CTR and other user response signal models for Search and Display ads.</li>\n</ul>\n<ul>\n<li>Design, prototype, and ship cutting-edge ML architectures (deep models, multi-task, transformer-based, LLM-assisted, multimodal).</li>\n</ul>\n<ul>\n<li>Define long-term modeling strategy and roadmap with clear business impact.</li>\n</ul>\n<p>Technical &amp; Engineering Execution</p>\n<ul>\n<li>Modernize our current modeling pipelines, addressing critical technical debt in data flows, training pipelines, and inference systems.</li>\n</ul>\n<ul>\n<li>Partner closely with engineering teams to improve reliability, monitoring, and performance of distributed training and online serving.</li>\n</ul>\n<ul>\n<li>Introduce best practices for experiment design, ablations, feature validation, and productionization.</li>\n</ul>\n<p>Business &amp; 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