| Microsoft Careers

Microsoft

Quick summary

Work type
On-site
Location
Washington
Salary
$119,800–$234,700 / yr
Posted
85 days ago
Closes
Sep 8, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $214k
This role $177k
$103k most similar roles pay here $280k

This role pays less than 75% of similar roles. Most pay $180,906–$246,150 — the shaded band above. At the midpoint, this role pays about $177k versus about $214k 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 310 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 285 roles with salary data.

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At a glance

TL;DR · | Microsoft Careers

As a Senior Applied AI Engineer specializing in Image Generation, you will join a dynamic and innovative team focused on developing cutting-edge AI assistant capabilities. Your primary responsibility will be to build and enhance image generation models using diffusion, GAN, and transformer-based techniques, while also curating large-scale datasets for training. You’ll implement evaluation frameworks to ensure model correctness and safety, run hillclimbing loops to optimize performance, and develop internal tools that accelerate the AI organization’s ability to deliver high-quality features. Additionally, you will integrate LLMs with product surfaces and APIs, build lightweight ML components, and collaborate closely with cross-functional teams to rapidly iterate on new capabilities based on user feedback. This role requires expertise in deep learning, model deployment at scale, and experience working in fast-paced startup environments, leveraging technologies such as Python, TensorFlow, PyTorch, and Kubernetes.

What you'll do

  • Train, fine-tune, and evaluate image generation models using diffusion, GAN, and transformer techniques.
  • Implement evaluation frameworks to assess correctness, safety, and UX quality of AI assistants.
  • Develop internal tools for prompt experimentation and model comparison telemetry in AI projects.
  • Integrate LLMs with product surfaces, APIs, and backend systems to enhance assistant features.
  • Optimize models for inference latency, throughput, and cost by applying techniques like quantization.
  • Build and maintain serving pipelines for real-time and batch image generation capabilities.

What we're looking for

  • 3+ years of experience in engineering, model building, evaluation, and data analysis.
  • Solid understanding of deep learning concepts including loss functions, optimization techniques, and regularization.
  • Experience deploying machine learning models at scale with inference optimization.
  • Familiarity with image preprocessing pipelines, data augmentation, and dataset curation.
  • Hands-on experience with hillclimbing AI evaluations to improve model performance.
  • Comfortable working in fast-paced startup environments on small teams.
  • Master’s Degree or equivalent practical experience required.

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