We are seeking a Senior Applied Scientist with expertise in natural language processing, deep learning, and Ads recommender systems. This role involves designing and implementing advanced machine learning models that enhance ad relevance and optimize user experiences across Microsoft Ads and Shopping platforms. The position is part of the Microsoft Artificial Intelligence (MAI)-Ads Engineering team, focusing on solving high-impact relevance problems. The successful candidate will have a significant impact on millions of users and advertisers.

• Bachelor's Degree in Data Science, Machine Learning, Statistics, Computer Science, or related field with 4+ years of related experience, or a Master's Degree with 3+ years, or a Doctorate with 1+ year of related experience.
• 6+ years of related experience in Data Science, Machine Learning, Statistics, Computer Science, or related field is preferred.
• 4+ years of working experience in statistical natural language processing (NLP) or Computer Vision (CV) with the latest deep learning technologies.
• 4+ years of experience coding in production systems using C++, C#, Java, or Python.

• Own high-impact relevance problem areas across Product Ads and Shopping.
• Drive algorithmic and modeling improvements using deep learning techniques from NLP and computer vision.
• Exercise solid technical judgment on metrics and evaluation strategies to optimize overall product ROI.
• Act as a technical leader and mentor, providing design reviews and documenting modeling guidance.
• Collaborate across disciplines to translate scientific intent into production-ready systems.
• Operate with high independence and accountability, anticipating risks and planning for unknowns.
• Contribute to ethics and privacy policies related to research processes and data collection.

• Employees at Microsoft are often offered comprehensive, “world-class” benefits—including health and mental-wellness programs, competitive pay with bonuses and stock awards, and retirement/savings options. Time-off and flexibility are common, with generous vacation and holidays, parental and caregiver leave, and flexible work schedules, alongside learning support, employee resource groups, product discounts, and matching-gifts/volunteering programs. Specific benefits can vary by region.