Applied Scientist II (AI)

TL;DR

Applied Scientist II (AI): Building and optimizing a large-scale, Azure-based intelligence platform for Microsoft Advertising, combining advanced machine learning with emerging LLM-powered agentic capabilities. With an accent on designing and developing scalable ML models, productionizing solutions, and integrating LLM-driven reasoning and summarization. Focus on applying statistical and machine learning techniques, prompt engineering for LLMs, and ensuring Responsible AI practices to directly influence advertiser experience and platform performance.

Location: Redmond, United States. Office attendance required 4 days per week for employees within a 50-mile commute of a U.S. Microsoft office, starting January 26, 2026.

Salary: USD $100,600 – $199,000 per year (U.S. national average); USD $131,400 – $215,400 per year (San Francisco Bay area and New York City metropolitan area).

Company

hirify.global is building a large-scale, Azure-based intelligence platform that transforms complex data into high-quality, actionable insights for Microsoft Advertising by combining advanced machine learning with emerging LLM-powered agentic capabilities.

What you will do

• Implement large-scale ML models for advertiser recommendations, insights, and forecasting.
• Apply statistical and machine learning techniques to detect patterns, surface anomalies, and generate data-driven insights.
• Collaborate with engineering and BI teams to operationalize models into dashboards and alerting systems.
• Support experimentation and contribute to model performance evaluation.
• Assist in prompt engineering for LLM calls and explore summarization techniques.
• Ensure Responsible AI practices and contribute to model governance.

Requirements

• Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field AND 2+ years of experience in statistics, predictive analytics, or research, OR a Master’s Degree in a related field AND 1+ year of experience, OR a Doctorate in a related field.
• Hands-on experience developing and validating ML/statistical models (e.g., regressions, classifiers, clustering).
• Experience with large-scale data processing or distributed computing (e.g., Spark, Azure Databricks).
• Familiarity with time-series analysis and anomaly detection techniques.
• Exposure to LLMs and prompt engineering for summarization or domain adaptation.

Culture & Benefits

• Work on cutting-edge applied science challenges that directly influence advertiser experience and platform performance.
• Opportunity to contribute to Microsoft's mission to empower every person and organization.
• Be part of a culture of inclusion, respect, integrity, accountability, and a growth mindset.
• Access to comprehensive benefits and compensation packages provided by Microsoft.