Senior Applied Scientist

Microsoft • Redmond, WA

13h • Hybrid

About The Position

We’re hiring a Senior Applied Scientist with expertise in natural language processing (NLP), deep learning, and Ads recommender systems in Redmond, WA or Mountain View, CA.
In this role, you will design and implement cutting-edge machine learning models and algorithms that power relevance systems across all surfaces for Microsoft Ads and Shopping including Bing, Copilot, and beyond.
You will have a direct impact on millions of users and advertisers, delivering scalable solutions to enhance ad relevance and optimize user experiences. This role is part of Microsoft Artificial Intelligence (MAI)-Ads Engineering and is responsible for the end-to-end relevance problem for our ads and shopping products.
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.
Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

Requirements

• Bachelor's Degree in Data Science, Machine Learning, Statistics, Computer Science or Computer Engineering or related field AND 4+ years related experience (e.g., statistics predictive analytics, research)
• OR Master's Degree in Data Science, Machine Learning, Statistics, Computer Science or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
• OR Doctorate in Data Science, Machine Learning, Statistics, Computer Science or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
• OR equivalent experience.

Nice To Haves

• Data Science, Machine Learning, Statistics, Computer Science 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 3+ years related experience (e.g., statistics, predictive analytics, research)
• OR equivalent experience.
• 4+ years working experience in statistical natural language processing (NLP) with the latest deep learning technologies including transformer and LLMs OR 4+ years working experience in Computer Vision (CV) with latest deep learning technologies including Vision Transformers.
• 4+ years working experience with coding in production systems using C++, C#, Java or Python.

Responsibilities

• Own high‑impact and open-ended relevance problem areas across Product Ads and Shopping including providing strategic direction to solve problems and applying deep subject matter knowledge to support business impact.
• Drive algorithmic and modeling improvements to the system using primarily deep learning techniques from NLP and computer vision, including latest LLM models, to deliver clear and measurable product impact
• Exercise solid technical judgment on metrics, evaluation strategies, and tradeoffs optimizing for overall product ROI rather than isolated metrics.
• Act as a technical leader and mentor, providing design reviews and documenting to share modeling guidance and evaluation best practices for other applied scientists to promote innovation.
• Collaborate deeply across disciplines (Engineering, PM, Research, Data Science), translating scientific intent into production‑ready systems and constraints.
• Operate with high independence and accountability, anticipating risks, planning for unknowns, and requiring minimal oversight to deliver sustained impact at scale.
• Use your deep understanding of fairness and bias to contribute to ethics and privacy policies related to research processes and data collection.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level