Overview

The Hardware Control Services (HCS) team within Microsoft’s Silicon Cloud Hardware Infrastructure Engineering (SCHIE) organization is responsible for building and operating world-class software and data-driven services that support Azure’s hardware infrastructure development. Our mission is to enable safe, reliable, and intelligent deployment of firmware payloads across the Azure fleet, ensuring system health and operational excellence at scale. As a Senior Software Engineer on this team, you will play a pivotal role in shaping the future of intelligent hardware control. You will develop and apply machine learning models and statistical techniques to optimize firmware deployment, detect anomalies, and improve fleet health monitoring. You will collaborate with software engineers, hardware teams, and product partners to design scalable solutions that drive efficiency and resilience across Azure’s global infrastructure. We are a software team embedded in a hardware organization, constantly innovating to meet the evolving needs of Azure’s expanding footprint. As our hardware architecture evolves, so does our software stack—and we are looking for scientists who thrive in fast-paced, cross-disciplinary environments. Qualifications

Required Qualifications: Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. 2+ years of experience in applied machine learning, data science, or statistical modeling. Other Requirements: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter. Preferred Qualifications: Proficiency in Python, R, or similar languages used for data science and ML development. Proven understanding of algorithms, data structures, and system design. Experience working with large-scale data pipelines and distributed systems Experience with cloud platforms (e.g., Azure, AWS, GCP) and deploying ML models in production environments. Familiarity with firmware, embedded systems, or hardware telemetry is a plus. Demonstrated ability to work in cross-functional teams and drive impact through collaboration. Proficient communication skills and a passion for solving complex, real-world problems. Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Microsoft will accept applications for the role until August 18, 2025.

#SCHIE #AZURE #Cloud Responsibilities

Design and implement machine learning models and statistical algorithms to improve firmware deployment safety, fleet health monitoring, and anomaly detection. Analyze large-scale telemetry and operational data to uncover insights and drive data-informed decisions. Collaborate with software engineers to integrate models into production services with high availability and performance. Partner with hardware and firmware teams to understand system behavior and identify opportunities for predictive analytics. Contribute to the architecture and design of next-generation intelligent control systems for Azure hardware. Participate in on-call rotations and contribute to service reliability and incident resolution. Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.Industry leading healthcareEducational resourcesDiscounts on products and servicesSavings and investmentsMaternity and paternity leaveGenerous time awayGiving programsOpportunities to network and connect