- Redmond, Washington, United States
- $102K–$202K per year
- 1+ years
Compensation
The typical base pay range for this role across the U.S. is USD $102,100 - $202,200 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 $133,800 - $219,200 per year.
Responsibilities
- Design and develop novel quantization and numerics algorithms to enable efficient deployment of LLM inference and training in Microsoft’s Azure production environments.
- Drive software development and model optimization tooling proof-of-concept effort to streamline deployment of quantized models.
- Analyze performance bottlenecks in quantized state-of-the-art LLM architectures and drive performance improvements.
- Prototype and evaluate emerging low-precision data formats through proof-of-concept implementations on novel hardware accelerator SDK.
- Co-design model architecture optimized for low-precision deployment in close collaboration with companywide AI/ML teams.
Requirements
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
- Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
- Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
- Nice to have: publications (patents, peer-reviewed academic papers)