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Tier-1 brand and Bangalore metro increase applicant density, but senior ML specialization limits broader competition.
Specialized ML/retrieval and ad-ranking experience required reduces cross-industry transferability.
Explicit degree-and-years minima plus required ML/LLM and production experience make filters stringent.
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Drive research and development for ad retrieval, matching, ranking, and generative machine learning models impacting Microsoft Ads platform at web scale.
Lead technical strategy, coach distributed teams, and influence cross-organization AI and ads ranking platform architecture and efficiency improvements.
Translate advanced AI research including LLMs, SLMs, and LRMs into production systems improving user experience and advertiser ROI.
Bachelor's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering or related and 6+ years experience, OR Master's degree and 4+ years experience, OR Doctorate and 3+ years experience in related fields.
Ability to pass Microsoft Cloud Background Check and comply with Microsoft security screening requirements.
Work Experience Required: Minimum applicable 3-6+ years depending on education level as above.
Not explicitly mentioned in the JD: Mandatory location, explicit onsite/remotely work mode, or notice period.
Senior applied scientist with 8+ years in machine learning including large-scale production model shipping and optimization experience.
Expertise with deep learning frameworks (PyTorch, TensorFlow, Hugging Face), distributed training, and recommendation system design at massive scale.
Experience influencing platform architecture and cross-team roadmap alignment, with a strong record of publishing in top AI/ML conferences (NeurIPS, ICML, KDD, ACL, etc.).