Microsoft Principal Hardware Engineer 

United States, Washington 

888285941

Required Qualifications

• 10+ years of technical engineering experience
  • OR Bachelor's degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 8+ years of technical engineering experience
  • OR Master's degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 5+ years of technical engineering experience
  • OR Doctorate degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 4+ years of technical engineering experience.

• 3+ years of experience in Computer Architecture or AI Systems.

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:

• MS/PhD in Machine learning, Computer Architecture/Systems, Electrical Engineering, High-Performance Computing or related areas.
• Experience in software/hardware co-design, specifically for AI Applications and GPU/Accelerator Architectures.
• Experience with CUDA or a related accelerator programming language.
• Understanding of fundamentals of AI workloads/applications.
• Hands on experience with frameworks such as Pytorch/Tensorflow/TensorRT.
• Deep knowledge of CNN/transformer architecture and optimization strategies – quantization, sparsity, sharding, KV Cache, Flash Attention.
• Solid programming skills in Python/C/C++.

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

Microsoft will accept applications for the role September 16, 2024.

• Analyse Hardware/Software Architecture for Business Critical AI workloads.
• Work with machine learning engineers, kernel engineers and compiler developers to understand needs and bottlenecks of high performance accelerators.
• Influence Hardware/System/Software roadmap of internal and external vendors to optimize them for Microsoft’ workloads.
• Benchmark GPUs and other AI hardware IPs.
• Drive Neural Network model/HW codesign.
• Develop performance estimates for critical kernels for different hardware configurations.
• Embody our