| Microsoft Careers

Microsoft

Hybrid

Quick summary

Work type
Hybrid
Location
Redmond, WA
Salary
$139,900–$274,800 / yr
Posted
63 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $181k
This role $207k
$101k most similar roles pay here $293k

This role pays more than 76% of similar roles. Most pay $155,000–$207,350 — the shaded band above. At the midpoint, this role pays about $207k 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

As a Principal Applied Scientist on the Signals Team at Microsoft Ads, you will design and implement large-scale machine learning models to predict user responses to advertisements, driving their deployment into production. Your daily tasks include running A/B tests, analyzing model impact on business KPIs, conducting data exploration for feature improvements, and establishing scalable pipelines for data processing and analytics. You will also mentor junior scientists and stay updated with the latest advancements in machine learning, applying them to enhance the modeling stack. The role requires expertise in transformer-based models, large language models (LLMs), and their production deployment, along with skills in LLM inference optimization and fine-tuning techniques such as SFT, LoRA, and RLHF. You will work within a complex multi-layered model environment, focusing on model quality and evaluation through robust frameworks that monitor for issues like bias and safety.

What you'll do

  • Design and implement large-scale machine learning models for text and numerical data.
  • Deploy machine learning models in production environments and monitor their performance.
  • Conduct A/B testing to analyze the impact of model metrics on business KPIs.
  • Develop scalable pipelines for data processing, analytics, training, and validation.
  • Track state-of-the-art approaches and implement them to improve existing modeling stack.
  • Mentor less experienced scientists on the team in machine learning practices.

What we're looking for

  • Deep experience designing, training, and optimizing large-scale machine learning models.
  • Proven ability to build high-performance LLM inference pipelines and apply advanced fine-tuning techniques.
  • Strong expertise in developing robust evaluation frameworks for ML and LLM systems.
  • Experience with transformer-based models and production deployment of machine learning models.
  • 5+ years of customer-facing, project-delivery experience in professional services or consulting.

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