Principal Software Engineer

Microsoft Microsoft · Big Tech · Mountain View, CA +2 · Software Engineering

Principal Software Engineer on the AI Frameworks team at Microsoft, responsible for developing and evaluating core algorithmic and hardware technologies for large-scale AI model training and inference on novel hardware. Collaborates with ML researchers, system engineers, and partners to optimize and scale AI models, build validation tools, and perform software development in languages like Python, C/C++, and CUDA.

What you'd actually do

  1. Collaborate broadly with ML researchers, system engineers, and production engineers.
  2. Engage with key partners to understand and evaluate performance and quality for state-of-the-art LLMs at different scales.
  3. Build software tools to support validation and exploration of LLM optimization technologies.
  4. Perform software development in model scripting and/or kernel languages, such as Python, C/C++, CUDA.
  5. Identify requirements, scope solutions, estimate work, schedule deliverables.

Skills

Required

  • Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience
  • coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • Ability to meet Microsoft, customer and/or government security screening requirements
  • Microsoft Cloud Background Check

Nice to have

  • Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience
  • Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience
  • Experience in training or serving Deep Neural Network models
  • Experience with Language Models and ML system optimization

What the JD emphasized

  • core algorithmic and hardware technologies
  • large scale inferencing and training
  • state-of-the-art LLMs
  • ML system optimization

Other signals

  • Develops AI software for training and deploying advanced AI models
  • Builds software stacks for supercomputers and AI accelerators
  • Optimizes and scales model training and inference
  • Works with OpenAI on Azure OpenAI service models
  • Enables large scale inferencing and training of advanced AI models on novel AI hardware