| Microsoft Careers

Microsoft

Hybrid

Quick summary

Work type
Hybrid
Location
Redmond, WA
Salary
$165,600–$296,400 / yr
Posted
54 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $181k
This role $231k
$99k most similar roles pay here $318k

This role pays more than 99% of similar roles. Most pay $155,000–$207,350 — the shaded band above. At the midpoint, this role pays about $231k 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

View all roles at Microsoft

At a glance

TL;DR · | Microsoft Careers

The Core Recommendation Ranking team at Microsoft AI Content Org seeks a Principal Applied Scientist to architect the next generation of recommendation systems using advanced AI technologies, particularly large language models and agentic systems. This senior technical leader will design robust machine learning pipelines for feature engineering, model training, evaluation, and online inference, driving innovation in deep learning architectures and multi-task learning. The role involves close collaboration with engineering, product, and applied science teams to integrate new capabilities into the ranking stack, ensuring seamless delivery of personalized content experiences for millions of users. Ideal candidates have expertise in recommendation systems, proficiency in modern ML frameworks like PyTorch and TensorFlow, and experience with large-scale data analytics tools such as Spark. They should also possess strong architectural skills and a track record of leading cross-functional initiatives, with publications in top-tier AI conferences preferred.

What you'll do

  • Architect next generation ranking and retrieval systems for large-scale content recommendation scenarios.
  • Design robust machine learning pipelines, including feature engineering and model training for efficient online inference.
  • Drive innovation in advanced model architectures like deep learning and LLM-enhanced ranking systems.
  • Mentor team members to foster a culture of scientific rigor and operational excellence.
  • Communicate team progress internally and evangelize technical advancements to management and leadership.

What we're looking for

  • Expertise in recommendation systems, ranking models, search relevance, or personalization.
  • Proficiency in modern ML frameworks (e.g., PyTorch, TensorFlow) and cloud-scale infrastructure.
  • Experience applying LLM techniques to recommendation systems.
  • Demonstrated ability to lead cross-functional initiatives and influence technical direction across teams.
  • Solid architectural skills for designing large-scale ML systems and distributed pipelines.
  • Experience with data structures, algorithms, and multi-tiered distributed services.
  • Publications in top-tier ML/AI conferences (e.g., NeurIPS, ICML).

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