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.
Work cross-functionally with data scientists and ML researchers/engineers across organizations to align on model accuracy and performance goals.
Partner with hardware architecture and AI software framework teams to ensure end-to-end system efficiency.
Qualifications
Required Qualifications
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience.
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 qualifications
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.
1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).
Demonstrated experience delivering production-grade software in areas such as model compression, low-precision numerics (FP8, INT8/4, NVFP4, MX formats, etc.), low-level kernel development, and performance optimization.
Proficiency with modern deep learning frameworks, including PyTorch, TensorFlow, TensorRT, and ONNX Runtime.
Expertise in GPU/NPU kernel development using CUDA, Triton, ROCm, or comparable frameworks and fast model bring up on a new stack
Strong understanding of Transformer and LLM architectures, with hands-on experience in optimization techniques such as quantization, pruning, tensor/parameter sharding, model parallelism, KV-cache optimization, and Flash Attention etc.
Practical experience with large-scale model evaluation, including benchmarking state-of-the-art LLMs and fine-tuning (SFT or RL) large models.
Strong programming skills in Python, C, and C++.
Excellent communication abilities and a proven capacity to collaborate effectively in hybrid team-oriented environments.
Hands-on experience implementing and optimizing low-level linear algebra routines, including custom BLAS kernels would be a plus.
Deep knowledge of mixed-precision arithmetic units, including numerical formats and microarchitecture, is highly desirable.
Strong written and verbal communication skills, with the ability to communicate complex technical ideas clearly and collaborate effectively across teams.
Applied Sciences IC3 - 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.
- 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
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. 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 with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.