| Microsoft Careers

Microsoft

Hybrid

Quick summary

Work type: Hybrid
Location: WA
Salary: $102,100–$202,200 / yr
Posted: 67 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $180k

This role $152k

$86k most similar roles pay here $251k

This role pays less than 70% of similar roles. Most pay $152,150–$207,350 — the shaded band above. At the midpoint, this role pays about $152k versus about $180k for comparable roles.

Based on 239 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 1580 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 1408 roles with salary data.

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At a glance

TL;DR · | Microsoft Careers

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As an Applied Scientist II on the IC3-AI team, you will collaborate with AI researchers and audio signal processing experts to design and build end-to-end machine learning systems for Microsoft’s Teams media stack. Your day-to-day responsibilities include developing ML pipelines that involve data cleaning, feature engineering, model training, and evaluation, as well as working across the product lifecycle from prototyping to deploying production-grade code optimized for performance and memory. You will also stay updated on the latest advancements in AI research and contribute to Microsoft’s intellectual property portfolio. The role requires expertise in machine learning algorithms, experience with data cleaning and feature engineering, and a strong background in statistics or computer science. Ideal candidates have published work and can effectively communicate complex ideas to both technical and non-technical audiences while contributing code to production systems.

Skills

Python TensorFlow PyTorch Scikit-learn Keras Jupyter Git CI/CD AWS Azure Google Cloud Docker Kubernetes MLOps PostgreSQL MongoDB Spark Hadoop CUDA NVIDIA GPUs Linux

What you'll do

Design and build end-to-end machine learning systems for human-human and human-AI interactions.
Develop machine learning pipelines including data cleaning, feature engineering, model training, and evaluation.
Optimize production-grade code for performance and memory efficiency across the product lifecycle.
Update deployed models based on A/B testing results to improve system effectiveness.
Stay current with AI advancements and contribute to intellectual property portfolio.

What we're looking for

Master's degree in a relevant field with at least 1 year of related experience, or equivalent.
PhD in a relevant field.
At least 2 years of experience developing and deploying machine learning algorithms.
Experience creating publications such as patents or peer-reviewed papers.
Ability to explain complex technical ideas to both technical and non-technical audiences.
Experience contributing code to production systems or shipped products.

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