Principal Applied Scientist
5 Months ago • 3-6 Years • $137,600 PA - $294,000 PA
Job Description
Microsoft AI Ads Engineering seeks a Principal Applied Scientist in Redmond, WA or Mountain View, CA to design and implement cutting-edge machine learning models (transformers, generative AI, reinforcement learning) for Microsoft Ads, Audience Network, and Copilot. This role requires developing scalable algorithms for content selection, user engagement, and ad generation, conducting A/B testing, building data pipelines, and staying abreast of AI research. The successful candidate will directly impact millions of users and advertisers by optimizing user experiences and ad relevance.
Good To Have:
- Generative AI, Reinforcement learning expertise
- Proven programming and data analysis skills
Must Have:
- Machine learning expertise (deep learning, transformers)
- Recommendation algorithms or NLP experience
- Experience with A/B testing and model evaluation
- Building scalable algorithms and data pipelines
- Bachelor's degree + 6 years exp. or Master's + 4 years exp. or PhD + 3 years exp.
Overview
We are hiring a Principal Applied Scientist in Redmond, WA or Mountain View, CA to join our Signals Modeling team, part of Microsoft AI (Artificial Intelligence) Ads Engineering organization, to shape the future of advanced AI at web scale.
In this role, the Principal Applied Scientist will design and implement state-of-the-art machine learning models and algorithms that power key systems within Microsoft Ads, Microsoft Audience Network, Copilot, and beyond. Their work will directly impact millions of users and advertisers by delivering scalable solutions that enhance ad relevance and optimize user experiences.
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.
Qualifications
Required Qualifications:
- Bachelor'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 Master'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 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.
- 3+ years of experience in Machine learning in deep learning projects.
- 3+ years of experience in recommendation algorithms or natural language processing.
Preferred Qualifications:
- Proven experience in programming and data analysis skills.
- Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, or transformers.
Applied Sciences IC5 - The typical base pay range for this role across the U.S. is USD $137,600 - $267,000 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $180,400 - $294,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
Microsoft will accept applications for the role until April 28, 2025.
#MicrosoftAI
Responsibilities
- Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot.
- Design scalable algorithms for online and offline systems, delivering innovative solutions for content selection, user engagement modeling, and ad generation.
- Drive experimentation through A/B testing and offline validation to evaluate model performance and refine user behavior predictions.
- Build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications.
- Stay at the forefront of AI research, incorporating the latest advancements to drive innovation and impact across Microsoft platforms.
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