{"id":2980519,"url":"https://alion.io/job/microsoft-senior-applied-scientist-ads-ranking-retrieval-2","title":"Senior Applied Scientist - Ads Ranking & Retrieval","company":{"id":18,"name":"Microsoft","domain":"microsoft.com","url":"https://alion.io/company/microsoft","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"B","score":83,"open_postings":363,"ghost_share":0,"stale_share":0.689,"repost_share":0.003,"time_to_fill_p50_days":29,"computed_at":"2026-10-30T05:48:23Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":26000,"max_usd":54000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":41},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Fine-tuning","optional":true},{"name":"Hugging Face","optional":true},{"name":"LLM","optional":true},{"name":"Post-training","optional":true},{"name":"PyTorch","optional":true},{"name":"Recommender Systems","optional":true},{"name":"TensorFlow","optional":true}],"status":"live","first_seen_at":"2026-08-07T12:47:06Z","employer_posted_date":"2026-08-18","last_verified_at":"2026-10-30T14:45:30Z","board_verified":true,"closed_at":null,"days_open":84,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":84},"description":"OverviewMicrosoft Ads powers one of the world’s largest digital advertising ecosystems, delivering billions of recommendations every day. We are seeking a Senior Applied Scientist who is passionate about advancing both frontier research and real-world product impact across our ad retrieval, matching, ranking, and generation systems.\nIn this role, you will drive innovation at the intersection of science and product, developing novel machine learning and AI approaches while ensuring they translate into measurable improvements for customers and the business. You will leverage and advance LLMs, SLMs, LRMs, and other state-of-the-art technologies to solve challenging problems at web scale. Your work will directly influence how ads are discovered, matched, ranked, and generated, improving user experience, advertiser ROI, and the efficiency of the Microsoft Ads platform.\nWe are looking for a scientist who values both deep research and practical execution. You are excited by scientific exploration, but equally motivated by shipping solutions, measuring impact, and iterating based on real-world outcomes. You thrive in collaborative, cross-functional environments and enjoy turning cutting-edge ideas into production systems that serve billions of requests.\nMicrosoft’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.\nResponsibilities\nAdvance research and development across retrieval, ranking, matching, and generative models.\nLeverage and improve SLMs/LLMs:/LRMs train, fine-tune, and align models and productionize them.\nEvolve the Ads ranking platform toward better usability, reliability, scalability, efficiency, and architectural coherence.\nProvide technical leadership on projects: set direction, coach a distributed team, and influence cross-org strategy.\nFollow research trends in AI to guide the group keep solutions state-of-the-art. - Collaborate with research and engineering teams.\nQualifications\nRequired/Minimum Qualifications:\nBachelor's 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 Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research).\nOR 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).\nOR equivalent experience.\n\nOther 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:\nMicrosoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter. \nPreferred Qualifications:\nMaster's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ 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).\nOR equivalent experience. \n\n6+ years of experience in ML with a proven record of shipping large-scale models to production.\nExpertise in training and inference optimization.\nProven ability to influence platform architecture and align cross-team roadmaps.\nTrack record of publications in tier-1 venues such as NeurIPS, ICML, KDD, WWW, ACL, SIGIR.\n5+ 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.\nExperience designing and scaling recommendation systems with massive query/item spaces and multi-stage ranking pipelines.\nProficiency with deep learning frameworks (e.g., PyTorch, Hugging Face, TensorFlow) and distributed training on large datasets.\nThis position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.\nMicrosoft 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. 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