We are the Deep Learning Platform team delivering the cutting-edge infrastructure in Microsoft AI. This is a core engineering team dealing with tens of thousands production servers, sub-millisecond latency and millions of Request Per Second (RPS) traffic. We develop advanced vector search algorithm, optimize deep learning model kernels, and build end to end large scale distributed deep learning serving system. Our system also leverage popular open source components including ONNX, PyTorch, Kubernetes, Docker, Kafka, g-RPC, etc. We work on wide range of CPU and GPU hardware for performance serving.
We are expanding our established deep learning vector databases service to largest scale in industry, in order to serve the growing demand of web search and retrieval for copilot. To do that, we are looking for a Principal Software Architect, Microsoft AI on performance analysis, key components scaling up, distributed system debugging, and new feature/algorithm development. The project collaborates with Microsoft Research team deeply. This is a great opportunity to work on a large production system with cutting-edge technology innovation.
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.
In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

REQUIRED QUALIFICATIONS:

• Bachelor’s Degree in Computer Science, or related technical discipline AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
• OR equivalent experience.

PREFERRED QUALIFICATIONS:

• Experience on distributed systems (e.g., communication optimization, network architecture design, network programming).
• Experience on high performance computing (e.g., cache/memory optimization, high-performance GPU programming, compiler-based optimization, fine-grained parallel library and runtime) or distributed systems (e.g., communication optimization, network architecture design, network programming).
• Theory and practice on the approximate nearest neighborhood search.
• Experience on deep learning model and large language model (LLM) serving.
• Experience on performance analysis and optimization for both CPUs and GPUs, as well as good understanding on software-hardware codesign.
  Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $133,600 - $256,800 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 $173,200 - $282,200 per year.
  Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay
  Microsoft will accept applications for the role until May 8, 2024.
  

  WWE# #MicrosoftAI

Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations

• Work on algorithms and methodologies in close collaboration with our research team, including problems in such domains as web-scale search, enterprise search, and document/multi-media search.
• Design and develop these search methodologies into production.
• Explore novel research topics in vector databases and deep learning that may inform our product strategy in the medium and long term.
• Work with customer to design solutions to meet customer their requirement.
• Embody our Culture and Values