Senior Researcher, Machine Learning

Microsoft

Quick summary

Work type
On-site
Location
Redmond, WA
Salary
$119,800–$234,700 / yr
Posted
123 days ago
Closes
Aug 23, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $210k
This role $177k
$103k most similar roles pay here $275k

This role pays less than 70% of similar roles. Most pay $174,076–$246,150 — the shaded band above. At the midpoint, this role pays about $177k versus about $210k 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 694 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 636 roles with salary data.

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At a glance

TL;DR · Senior Researcher, Machine Learning

As a Senior Researcher - Machine Learning at Microsoft Research's Health Futures division, you will join a global team dedicated to advancing the intersection of AI and healthcare. Your primary responsibilities include designing and implementing innovative methodologies for scientific discovery through artificial intelligence, focusing on areas such as post-training optimization, inference-time efficiency, and interpretability. You will leverage state-of-the-art deep learning techniques to fine-tune models for specific applications and develop systems that optimize interaction patterns with these models during inference. Ideal candidates possess a doctorate or equivalent experience in a relevant field and have a passion for making groundbreaking discoveries in the life sciences domain. Preferred qualifications include expertise in generative AI, deep learning model optimization, and creating robust research artifacts within interdisciplinary teams.

What you'll do

  • Design and implement novel methodologies for scientific discovery using artificial intelligence.
  • Evaluate and fine-tune deep learning models for specific application scenarios.
  • Develop approaches to optimize inference time interactions with deep learning models.
  • Create and use generative AI techniques in the life sciences to solve real-world problems.
  • Innovate software, systems, or workflows that leverage AI-based solutions in biomedicine.

What we're looking for

  • Doctorate in a relevant field or equivalent experience with extensive research background.
  • Deep expertise in artificial intelligence and machine learning methodologies.
  • Proven experience in developing and applying generative AI techniques to life sciences challenges.
  • Strong track record in optimizing deep learning models for inference-time performance.
  • Experience innovating software, systems, or workflows using AI-based solutions for real-world problems.

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