Microsoft Software Engineer II 

United States, Washington 

139539942

Required Qualifications

• Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

  • OR equivalent experience.

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/Additional Qualifications:

• Proven experience as a DevOps Engineer or in a similar role.
• Experience with cloud platforms such as Azure.
• Proficiencyin scripting languages such as Python, Bash, or PowerShell.
• Solid understanding of CI/CD pipelines and tools like Azure DevOps.
• Familiarity with containerization technologies like Docker and Kubernetes.
• Excellent problem-solving skills and attention to detail.
• Solid communicationand collaboration skills.
• Working knowledge of prevailing LLM models and frameworks likeTensorflow,Pytorchis a plus.
• Experience with monitoring tools like Splunk, Prometheus, and Grafana.
• Familiarity with visualization and reporting tools like PowerBI is a plus.
• Experience with agile methodologies and practices.

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 January 6, 2025.

• Develop in-house performance modeling tool for Machine Learning Systems.

• Identify performance bottlenecks, optimize resource utilization, and implement improvements to enhance performance.

• Integrate CI/CD pipelines into the software development process.

• Design and maintain databases for large-scale design-space exploration experiments.

• Automation and tooling to enable data upload from experiments to cloud storage for efficient data retrieval and querying.

• Come up with dashboards to maintain performance visualization and build infrastructure for improving the analysis framework.

• Guide teams in designing, building, testing, and deploying changes to existing software.

• Identify manual processes that can be automated.

• Consider the organization’s entire infrastructure when making changes and improvements.

• Maintain and improve the org’s infrastructure.

• Implement, install, upgrade, troubleshoot, and manage the configuration and maintenance of codebase.

• Collaborate with team members to define product requirements and implementation.

• Embody our