Principal Applied Scientist

Job Description Microsoft Ads powers one of the world's largest digital advertising ecosystems, delivering billions of recommendations every day. We are seeking a Principal Applied Scientist to define and advance R&D of retrieval, matching, ranking, and generation algorithms across our ad recommendation systems. In this role, you will shape the science and innovation strategy by leveraging and improving LLM/SLM/LRM and productionize breakthroughs at web scale. Your work will directly influence how ads are discovered, matched, and generated improving user experience, advertiser ROI, and the efficiency of the entire ads platform. 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. Responsibilities - Advance research and development across retrieval, ranking, matching, and generative models. - Leverage and improve SLMs/LLMs:/LRMs train, fine-tune, and align models and productionize them. - Evolve the Ads ranking platform toward better usability, reliability, scalability, efficiency, and architectural coherence. - Provide technical leadership on projects: set direction, coach a distributed team, and influence cross-org strategy. - Follow research trends in AI to guide the group keep solutions state-of-the-art. - Collaborate with research and engineering teams. Qualifications Required Qualifications: - Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ 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 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 5+ years related experience (e.g., statistics, predictive analytics, research) - OR equivalent experience. - 8+ years of experience in ML with a proven record of shipping large-scale models to production. - Hands-on experience with SLM/LLM /LRM training, fine-tuning, and post-training. - Experience designing and scaling recommendation systems with massive query/item spaces and multi-stage ranking pipelines. - Proficiency with deep learning frameworks (e.g., PyTorch, JAX, TensorFlow) and distributed training on large datasets. Other Requirements Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: - Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter. Preferred Qualifications - Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 12+ years related experience (e.g., statistics, predictive analytics, research) - OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research) - OR equivalent experience. - 10+ years of experience in ML with a proven record of shipping large-scale models to production. - Expertise in training and inference optimization. - Proven ability to influence platform architecture and align cross-team roadmaps. - Track record of publications in tier-1 venues such as NeurIPS, ICML, KDD, WWW, ACL, SIGIR. #MicrosoftAI Microsoft is an equal opportunity employer. Consistent with applicable law, 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 and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.