Multimodal | Microsoft Careers

Microsoft

Closes today Hybrid

Quick summary

Work type
Hybrid
Location
Salary
$119,800–$234,700 / yr
Posted
179 days ago
Closes
Jun 6, 2026 (soon)

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $180k
This role $177k
$106k most similar roles pay here $248k

This role pays more than 53% of similar roles. Most pay $152,150–$208,800 — the shaded band above. At the midpoint, this role pays about $177k 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 728 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 664 roles with salary data.

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At a glance

TL;DR · Multimodal | Microsoft Careers

Join Microsoft’s Multimodal team as a senior engineer or scientist to build one of the world’s most advanced foundation models. You will develop algorithms, model architectures, and data pipelines while improving training and deployment efficiency in a fast-paced environment. Key responsibilities include conducting experiments, innovating datasets, and collaborating closely with infrastructure, data engineering, and product teams. Required skills encompass strong analytical abilities, experience with large-scale distributed systems, and proficiency in languages like Python, along with familiarity with ML frameworks such as PyTorch and TensorFlow. Preferred qualifications include expertise in multimodal dataset design, curation, and annotation pipelines, as well as background in LLM interaction and deployment, ensuring a rigorous data-driven approach to shaping the future of AI at Microsoft.

What you'll do

  • Develop algorithms and model architectures for advanced foundation models.
  • Conduct experiments and champion measurement and evaluation processes.
  • Innovate datasets and data pipelines for large-scale distributed systems.
  • Improve training and deployment efficiency with a rigorous data-driven approach.
  • Collaborate on infrastructure, data engineering, pre-training, post-training initiatives.

What we're looking for

  • Proven expertise in large-scale distributed systems and scalable architectures.
  • Experience with ML frameworks like PyTorch and TensorFlow, and cloud environments such as Azure.
  • Strong background in data engineering for foundation models, including dataset design and curation.
  • Practical experience in prompt engineering and deployment of conversational AI systems.
  • Demonstrated ability to collaborate across cross-functional teams and communicate effectively.
  • Bachelor's degree in a relevant technical field plus 4+ years of coding experience.

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