Facebook Software Engineer Systems ML - SW/HW Co-design 

United States, California, Sunnyvale 

683665228

Apply relevant AI infrastructure and hardware acceleration techniques to build & optimize our intelligent ML systems that improve Meta’s products and experiences

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

Mentor other engineers / research scientists & improve the quality of engineering work in the broader team

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

Specialized experience in one or more of the following machine learning/deep learning domains: 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

A Bachelor's degree in Computer Science, Computer Engineering, relevant technical field and 7+ years of experience in AI framework development or accelerating deep learning models on hardware architectures OR a Master's degree in Computer Science, Computer Engineering, relevant technical field and 4+ years of experience in AI framework development or accelerating deep learning models on hardware architectures OR a PhD in Computer Science Computer Engineering, or relevant technical field and 3+ years of experience in AI framework development or accelerating deep learning models on hardware architectures.

Experience with distributed systems or on-device algorithm development

Experience with recommendation and ranking models

Technical leadership experience