| Microsoft Careers

Microsoft

Quick summary

Work type: On-site
Location: USSan Francisco, CANew York, NY
Salary: $139,900–$274,800 / yr
Posted: 70 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $180k

This role $207k

$101k most similar roles pay here $293k

This role pays more than 78% of similar roles. Most pay $152,150–$207,350 — the shaded band above. At the midpoint, this role pays about $207k 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 1577 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 1405 roles with salary data.

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At a glance

TL;DR · | Microsoft Careers

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As a Principal Applied Scientist at Microsoft Copilot Studio, you will join the Applied Science and Research team to drive innovation in AI and machine learning. Your role involves designing and implementing advanced AI architectures for Large Language Models (LLMs) and developing robust evaluation frameworks to ensure model performance meets customer standards. You will build internal tools to streamline fine-tuning workflows and automate tasks within secure environments, while also contributing to the translation of cutting-edge research into practical solutions that enhance product quality and customer experiences. This position requires expertise in machine learning algorithms, data science, software engineering, and a deep understanding of AI subfields such as NLP and generative models. Preferred qualifications include experience with MLOps workflows, modern LLMOps frameworks like LangChain and PromptFlow, and a background in applied AI or NLP research.

Skills

Python Java C++ TensorFlow PyTorch Kubernetes Docker CI/CD MLOps LangChain PromptFlow GitHub Copilot PostgreSQL Redis AWS Azure Google Cloud Platform NLP Deep Learning Reinforcement Learning RAG Multimodal Models

What you'll do

Design and implement AI architectures for improving Large Language Models (LLM) inference systems, including RAG and multi-agent setups.
Develop robust evaluation frameworks to assess model performance and address identified weaknesses in compliance with customer standards.
Build internal tools to streamline model fine-tuning and evaluation workflows within secure development environments.
Prepare and analyze data for machine learning, identifying optimal features and addressing data gaps.
Implement large-scale model fine-tuning techniques for both closed and open source LLMs and SLMs to solve real-world problems.
Provide deep expertise in AI subfields like Generative AI, NLP, and reinforcement learning to translate research into practical solutions.

What we're looking for

Bachelor's degree in a relevant field plus at least 6 years of related experience, or equivalent.
Deep expertise in machine learning, data science, and software engineering to solve complex problems.
Experience with MLOps workflows including CI/CD, monitoring, and retraining pipelines.
Familiarity with modern LLMOps frameworks such as LangChain and PromptFlow.
3+ years of experience conducting applied AI or NLP research in academic or industry settings.
Strong background in developing and deploying live production systems or AI services.

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