Microsoft Principal Software Engineering Manager-AI Platform 

United States, Washington 

415766414

I acrossOur stack enables ML developers toand scale out model trainingand inference.  We work directly with OpenAI on the models hosted on the Azure OpenAI service.

As a member of this team, you will have the opportunity to work on multiple levels of the AI software stack, including the fundamental abstractions, programming models, compilers, runtimes,and APIs to enable large scale training and inferencing of models.

This is a technical management role: it requires managinglooking for someone who has a demonstrated history of solving hard technical problems and is motivated to tackle the hardest problems in building a full end-to-end AI stack.  An entrepreneurial approach and ability to take initiative and move fast are essential.

Required Qualifications:

• Bachelor's Degree in Computer Science, or related technical discipline AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

  • OR equivalent experience.

• 8+ years of software development experience

• 8+ years' experience with C/C++
• 8+ years of technical leadership experience in a software team

Preferred Qualifications:

• Technical background and solid foundation in software engineering principles and architecture design

• Ability to plan and influence technical designs on projects that will have potential long-term impact to Microsoft.

• Exposure to Deep Neural Network training and inference and experience in one or more deep learning frameworks (PyTorch, TensorFlow, ONNX, etc.)

• Great cross-team collaboration skills and the desire to collaborate in a team of researchers and developers
• Communicationskills (both written and oral)

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

• Manage and lead engineering team.

• Apply engineering principles for defining robust and maintainable architectures and designs.

• Collaborate broadly across multiple disciplines from hardware designers to ML developers.

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

• Technical leadership and mentoring of software engineers.

• Other

  • Embody our