Senior Applied Scientist

Microsoft

Hybrid

Quick summary

Work type
Hybrid
Location
Salary
$119,800–$234,700 / yr
Posted
38 days ago

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $188k
This role $177k
$106k most similar roles pay here $248k

This role pays more than 51% of similar roles. Most pay $162,000–$213,931 — the shaded band above. At the midpoint, this role pays about $177k versus about $188k for comparable roles.

Based on 240 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 622 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 571 roles with salary data.

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At a glance

TL;DR · Senior Applied Scientist

Join our cutting-edge team as a senior machine learning engineer, where you will lead the design and development of large-scale recommendation, ranking, personalization, and generative AI systems across Microsoft’s consumer ecosystem. You’ll drive technical strategy for retrieval, ranking, reranking, whole-page optimization, and LLM-powered experiences while developing state-of-the-art models for engagement optimization and trust-aware personalization. This role involves leading innovation in multi-agent systems, reinforcement learning, and context-aware recommendation technologies, partnering with cross-functional teams to deliver high-impact AI-driven user experiences. Preferred qualifications include a Master’s or Doctorate in Computer Science or related fields, experience with deep learning frameworks like PyTorch or TensorFlow, and expertise in large-scale distributed systems and billion-scale user systems.

What you'll do

  • Lead the design and development of large-scale recommendation, ranking, and personalization systems for Microsoft consumer products.
  • Drive technical strategy and architecture for retrieval, ranking, reranking, whole-page optimization, and LLM-powered experiences.
  • Develop state-of-the-art machine learning models to optimize user engagement, satisfaction, monetization, and trust.
  • Innovate in generative AI, multi-agent systems, reinforcement learning, and context-aware recommendation technologies.
  • Define and implement multi-objective optimization frameworks balancing user engagement, quality, diversity, trust, and revenue.

What we're looking for

  • Bachelor's degree in Computer Science or related field with 4+ years of experience, or equivalent.
  • Proven experience in machine learning, recommender systems, ranking, search, and personalization.
  • Experience building and deploying large-scale production ML systems.
  • Proficiency with deep learning frameworks like PyTorch or TensorFlow.
  • Understanding of experimentation, metrics, and model evaluation techniques.
  • Track record of technical leadership and cross-functional influence in AI projects.

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