- Apply relevant AI infrastructure and hardware acceleration techniques to build & optimize our intelligent ML systems that improve Meta’s products and experiences
- Develop high performance kernels and different parallelism techniques to improve E2E performance.
- Goal setting related to project impact, AI system design, and infrastructure/developer efficiency
- Directly or influencing partners to deliver impact through deep, thorough data-driven analysis
- Drive large efforts across multiple teams
- Define use cases, and develop methodology & benchmarks to evaluate different approaches
- Apply in depth knowledge of how the ML infra interacts with the other systems around it
- Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
- Currently has, or is in the process of obtaining, a PhD degree in Computer Science, Computer Vision, Generative AI, NLP, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
- Specialized experience in one or more of the following machine learning/deep learning domains: Model compression, hardware accelerators architecture, GPU architecture, machine learning compilers, or ML systems, AI infrastructure, high performance computing, performance optimizations, or Machine learning frameworks (e.g. PyTorch), numerics and SW/HW co-design
- Experience developing AI-System infrastructure or AI algorithms in C/C++ or Python
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
- Experience or knowledge of training/inference of Large scale AI models
- Experience or knowledge of distributed systems or on-device algorithm development
- Experience or knowledge of recommendation and ranking models
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