Microsoft Senior Software Engineer - AI Compilers 

United States, Washington 

93927533

The AIused to trainand deployand design newprogramming abstractionsandAI hardwareat the intersection ofprogramming languagealgorithmic innovation,nd high-performance computing.Our culture is highlyandpartner withhardware architectsplatform engineers,andsoftware groupsalso enthusiasticallyto build AIthat everyone can

andSeniorAI Compiler effort.miss thisworking onthat has

Required Qualifications:

• Bachelor’s degree in computer science, or related technical discipline 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.
• 3+ years’ experience with C++.
• 2+ years’ experience building compilers, using compiler frameworks like LLVM/MLIR, or optimizing AI/numerical workloads.

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:

• 2+ years’ experience with Python.
• M.S. or Ph.D. in computer engineering or related fields, or equivalent industry experience.
• Experience using or developing Machine Learning training or inference software.
• A deep curiosity and interest about exploring new technologies.
• Effective cross-team collaboration skills and communication skills.

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 July 5, 2024.

• Design and develop AI softwarein C/C++, Python, and other languages.

• mplementinginnovative newcompiler features and optimization

• eveloping code generation techniques for novel hardware platforms

• ptimizingAI workloads

• Designing new programming abstractions for AI

• ingbroadly across multiple disciplines from hardwarearchitectsto ML developers

• requirements, scope solutions, estimate work, schedule deliverables.

• establishand drive the adoption of outstanding coding standards and patternsandhelp enhance ourinclusiveengineering culture.

Other:

• Embody our and