Principal Applied Scientist, Copilot Quality

Microsoft

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: —
Salary: $165,600–$296,400 / yr
Posted: 3 days ago
Freshness: Confirmed live today
Closes: Apr 21, 2027

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $217k

This role $231k

$136k $314k

below market most similar roles pay here above market

This role pays more than 62% of similar roles. Most pay $177,250–$256,000 — the blue band above. At the midpoint, this role pays about $231k versus about $217k 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 651 roles with salary data.

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At a glance

TL;DR · Principal Applied Scientist, Copilot Quality

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As a Principal Applied Scientist within the Copilot organization, you will lead the strategy and technical roadmap for building a robust quality system for AI assistants. You will be responsible for developing online and offline metrics, representative evaluation datasets, and human and AI-assisted labeling approaches grounded in real customer tasks. Your daily work involves identifying high-impact failure modes, performing root cause analysis, and implementing hill-climbing approaches such as post-training, retrieval, ranking, prompting, and orchestration. You will design rigorous A/B experiments and quality gates to ensure reliability, safety, and performance. The role requires expertise in statistics, predictive analytics, deep learning, reward modeling, and reinforcement learning to solve the technical challenge of turning customer signals into verified product improvements for large language models.

What does a Applied Scientist earn?

Median $208800 from 61 postings across 10 companies.

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Skills

Machine Learning Large Language Models Deep Learning Reinforcement Learning Retrieval Ranking Post-training Reward Modeling Statistics Predictive Analytics Model Evaluation AI Safety

What you'll do

Develop online and offline metrics, evaluation datasets, and benchmarks grounded in real customer tasks.
Validate that quality measures are statistically sound and predictive of actual customer outcomes.
Identify high-impact failure modes using data, evaluations, and customer feedback to determine root causes.
Improve quality through post-training, retrieval, ranking, prompting, orchestration, and product changes.
Design experiments to distinguish offline results from actual improvements in customer satisfaction and task success.
Establish rigorous A/B experimentation, quality gates, and regression protection for product rollouts.
Create operating mechanisms to rapidly resolve quality tradeoffs, dependencies, and release risks.

What we're looking for

Bachelor's degree and 8+ years of experience in statistics, predictive analytics, or research.
Master's degree and 6+ years of experience in statistics, predictive analytics, or research.
Doctorate and 5+ years of experience in statistics, predictive analytics, or research.
Equivalent experience to the degree and years of experience requirements.
Advanced degree in a relevant technical discipline (preferred).
Experience improving large language models, AI assistants, agents, or other large-scale AI products (preferred).
Significant experience building, evaluating, or improving production ML or AI systems (preferred).
Expertise in large-model evaluation, deep learning, post-training, reward modeling, reinforcement learning, retrieval, or ranking (preferred).

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