| Microsoft Careers

Microsoft

Hybrid

Quick summary

Work type: Hybrid
Location: Redmond, WA
Salary: $119,800–$234,700 / yr
Posted: 63 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $181k

This role $177k

$106k most similar roles pay here $248k

This role pays more than 60% of similar roles. Most pay $155,000–$207,350 — the shaded band above. At the midpoint, this role pays about $177k versus about $181k for comparable roles.

Based on 238 similar postings.

Employer

About Microsoft

Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing

Microsoft currently has 1103 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 985 roles with salary data.

Most-posted roles

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At a glance

TL;DR · | Microsoft Careers

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As a Senior Applied Scientist on Microsoft’s Signals Modeling team within AI Ads Engineering, you will design and implement advanced machine learning models to enhance ad relevance and user experiences across platforms like Microsoft Ads and Copilot. Your daily tasks include developing cutting-edge algorithms for ads selection and generation, building scalable data pipelines, and conducting rigorous offline and online evaluations through A/B testing. You will work closely with engineers to deliver high-performance real-time inference systems, requiring expertise in generative AI, deep learning, reinforcement learning, and transformers. This role demands proficiency in Python or similar languages, along with a strong background in large-scale machine learning deployments and data analysis.

Skills

Python TensorFlow PyTorch Keras Scikit-learn Pandas NumPy Docker Kubernetes AWS Azure CI/CD A/B Testing Reinforcement Learning Generative AI Transformers LLM SQL PostgreSQL MongoDB

What you'll do

Develop and deploy cutting-edge ML models to optimize user interactions and ad relevance.
Design scalable algorithms for ads selection, generation, and relevance across online/offline systems.
Drive experimentation through A/B testing and offline validation to refine model performance.
Build robust data pipelines for handling large-scale datasets in advanced AI applications.
Stay updated with the latest AI research to drive innovation and impact at Microsoft.

What we're looking for

Proven experience in developing and deploying large-scale machine learning models.
Expertise in generative AI, deep learning, reinforcement learning, and transformers.
Strong programming skills for data analysis and algorithm development.
Experience with A/B testing and offline validation to evaluate model performance.
Ability to design scalable algorithms for online and offline systems.
Knowledge of building robust data pipelines for large-scale datasets.

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