Principal Software Engineer, CoreAI

Microsoft

Quick summary

Work type: On-site
Location: —
Salary: $165,600–$296,400 / yr
Posted: 69 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $196k

This role $231k

$124k most similar roles pay here $315k

This role pays more than 83% of similar roles. Most pay $169,625–$222,600 — the shaded band above. At the midpoint, this role pays about $231k versus about $196k 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 622 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 559 roles with salary data.

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At a glance

TL;DR · Principal Software Engineer, CoreAI

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As a Principal Software Engineer on the GenAI Infrastructure and Solutions team, you will lead the development of large-scale training infrastructure and tools for various AI models including LLMs, SLMs, multimodal, and code-specific models. Your responsibilities include collaborating with engineers and researchers to optimize training infrastructures, designing highly scalable and reliable services, ensuring security and privacy compliance, and enhancing engineering systems in complex cloud environments. You will also contribute to the deployment and monitoring of these services in production. The ideal candidate has extensive experience in coding languages such as C++, Java, Python, and familiarity with distributed systems, containerization tools like Docker and Kubernetes, and DevOps practices including CI/CD pipelines. This role involves working on cutting-edge AI technologies at scale within a dynamic team environment focused on innovation and quality software delivery.

Skills

Python Docker Kubernetes CI/CD DevOps C C++ C# Java JavaScript distributed systems cloud-based infrastructure containerization tools virtualization technology production ML systems model serving caching batching monitoring

What you'll do

Lead the development of training infrastructure for large language models and other AI models.
Design and enhance scalable and reliable services for AI platforms.
Implement secure and privacy-compliant services to serve production traffic.
Improve engineering practices to ensure service quality in complex cloud environments.
Contribute to the deployment and monitoring of AI services in production.

What we're looking for

8+ years of technical engineering experience with coding in languages such as C++, Java, Python.
6+ years of experience designing, developing, and shipping high-quality software.
3+ years of experience with distributed systems and cloud-based infrastructure.
2+ years of experience with containerization tools like Docker and Kubernetes.
2+ years of experience in DevOps practices including CI/CD and automated testing.
Familiarity with production ML systems, model serving, caching, batching, and monitoring.
Bachelor's Degree in Computer Science or related technical field.

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