Microsoft Software Engineer 

United States, Washington 

417233553

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mission is to power, protect, and transform the employee experience at Microsoft across the globe.  Come, build community, explore your passions, pursue your AI and ML aspirations, do your best work. Microsoft Digital (MSD), is the team that innovates, creates, and delivers the vision for Microsoft’s employee experience, human resources, corporate and legal affairs, global real estate products, and runs Microsoft’s internal network and infrastructure, plus builds campus modernization and hybrid solutions. You willGen AI, AI, ML, and other topical and latest technologies to focus on empowering Microsoft employees with the tools and services that define both the physical and digital future of work.

with afoundation in software development andskills to join our dynamic team. In this role, you will support thedesign andof AI solutionsusing Azurecloud infrastructureAzure DevOps tools and practices. This role will alsoexciting opportunities to work on AI-driven automation solutions, where you willmachine learning and AI tools toprocesses, improve operational efficiency, and enhance our DevOps pipeline.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Required Qualifications:

• Bachelor's Degree in Computer Science, or related technical discipline with proven experience in Python, DAX, C#, Power BI or Power Query
  • OR equivalent experience.
• Experience with one of the following: AI, Machine Learning, Gen AI or NLP
• Experience with big data processing systems or online services.
• Experience with cloud platforms such as Azure or similarplatforms.

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:

• Bachelor's Degree in Computer Science OR related technical field AND 1+ year(s) technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, OR Python
  • OR Master's Degree in Computer Science or related technical field with proven experience coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience.
• Proficiencyin Agile software deliveryutilizingAzure DevOps Service.

Software Engineering IC2 - The typical base pay range for this role across the U.S. is USD $81,900 - $160,200 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 $105,600 - $174,600 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 December 19, 2024.

• Innovate and bringcutting edgesolutions to run AI models at scale, intelligent data packingforLLM/SLM, orchestrating between different AI components.
• With guidance from others, you’ll contribute to the development of data tools that can transform, manage, and access data. You’ll also validate code to test availabilityand data qualitypolicies.
• Follow data modeling and handling procedures to maintain compliance with all applicable laws and policies across your assigned workstreams. You’ll also learn about permissions and approvals for data access within a data pipeline.
• Act as a Designated Responsible Individual (DRI) in monitoring system/product feature/service for degradation, downtime, or interruptions for simple problems, and recommends actions to restore system/product/service by following the playbook.
• Review current developments and proactively seeks new knowledge that will improve the availability, reliability, efficiency, observability, and performance of products while also driving consistency in monitoring and operations at scale.

• Embody our and