Machine Learning Engineer

Microsoft

Hybrid

Quick summary

Work type
Hybrid
Location
—
Salary
$100,600–$199,000 / yr
Posted
82 days ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $213k
This role $150k
$82k most similar roles pay here $277k

This role pays less than 89% of similar roles. Most pay $179,356–$246,150 — the shaded band above. At the midpoint, this role pays about $150k versus about $213k 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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View all roles at Microsoft

At a glance

TL;DR · Machine Learning Engineer

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As a senior software engineer on the generative AI team, you will design, build, and operate production-grade systems that power customer-facing AI services at global scale. Your day-to-day involves contributing to core capabilities such as retrieval-augmented generation and context engineering, while ensuring robust testing and monitoring practices are in place. You will work closely with security and compliance teams to meet enterprise requirements and Responsible AI standards, collaborating across product and research teams to deliver secure, performant improvements. The role requires expertise in machine learning engineering, experience with MLOps in cloud environments like Azure, and a strong background in software development for complex systems. Ideal candidates have advanced degrees in Computer Science or related fields and a track record of delivering enterprise AI products at scale.

Skills

GenerativeAI MultimodalSystems MLOps Azure PromptEngineering RAG MemoryFrameworks CI/CD Python Java C++ SQL PostgreSQL Docker Kubernetes Terraform AWS Git Jenkins GitHub Swagger/OpenAPI RESTfulAPIs JSON YAML Prometheus Grafana Kafka Redis Elasticsearch GraphQL

What you'll do

  • Design and build production-grade generative AI and multimodal systems from implementation to live operations.
  • Optimize core GenAI capabilities by balancing quality, latency, cost, and safety through data-driven decisions.
  • Enhance model and system quality using evaluation frameworks, experiment design, and production telemetry.
  • Develop secure solutions meeting enterprise requirements and aligning with Responsible AI standards.
  • Work closely with product teams to translate customer needs into well-designed APIs and developer experiences.

What we're looking for

  • 3+ years of experience in software engineering, machine learning, or applied AI.
  • Experience building and shipping generative AI systems, including multimodal scenarios.
  • Proficiency in MLOps practices for cloud environments (Azure preferred).
  • Advanced degree in Computer Science, Machine Learning, or related field.
  • Strong background in prompt engineering, retrieval-augmented generation, and memory frameworks.
  • Track record of delivering enterprise-scale AI products with compliance and security standards.

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