Senior Applied Scientist, CoreAI

Microsoft

Quick summary

Work type: On-site
Location: —
Salary: $119,800–$234,700 / yr
Posted: 66 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $193k

This role $177k

$106k most similar roles pay here $248k

This role pays less than 55% of similar roles. Most pay $162,000–$223,331 — the shaded band above. At the midpoint, this role pays about $177k versus about $193k 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 622 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 571 roles with salary data.

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At a glance

TL;DR · Senior Applied Scientist, CoreAI

Role Posting Log in to save

Join the Azure AI Knowledge team as a senior engineer or scientist to drive the development of agentic retrieval systems that integrate structured and unstructured enterprise data into knowledge bases. You will work on developing LLM prompts, agents, and query execution workflows with tight latency constraints, while also collecting and filtering training data for complex queries requiring reasoning. Your day-to-day involves incorporating state-of-the-art research into production techniques, building metrics across search engine components, and integrating customer feedback to enhance dataset construction and evaluation. You will collaborate closely with product management, engineers, and other functions to advance technical excellence through experimentation infrastructure and proofs of concept using AI coding agents. Ideal candidates have a strong background in statistics, computer science, or related fields, experience with agentic coding systems, and the ability to define task-specific metrics and datasets.

Skills

Azure Python LLM Kubernetes Terraform Docker CI/CD Prometheus Grafana RAG PostgreSQL Redis Git Jenkins Ansible Hadoop Spark TensorFlow PyTorch

What you'll do

Independently incorporate state-of-the-art research into production techniques.
Develop metrics for all search engine components to enhance performance.
Integrate customer feedback into dataset construction and technique development.
Contribute to experimentation infrastructure using AI coding agents.
Ensure the team’s experimental codebase is efficient and repeatable.
Drive clear and efficient plans, documents, and communication within the team.

What we're looking for

Bachelor's degree in a relevant field plus 4+ years of experience or higher-level degrees with fewer years of experience.
Experience incorporating state-of-the-art research into production techniques.
Ability to develop and use metrics across search engine components.
Skill in leveraging customer feedback for dataset construction and evaluation.
Proficiency in driving technical excellence through experimentation infrastructure.
Strong collaboration skills, including hybrid and asynchronous teamwork.
Experience with agentic coding systems and defining task-specific metrics.

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