Meta is seeking an experienced Machine Learning ASIC Engineer to join their Infrastructure organization in a role that combines cutting-edge AI/ML with hardware architecture. This position offers an exciting opportunity to work on developing state-of-the-art machine learning accelerators for data center efficiency.
The role involves working with AI/ML and video codec experts to architect and build accelerators for top workloads, enabling Meta's data centers to scale efficiently. You'll be part of an ASIC team focused on creating "Green" data center accelerators, contributing to both the architecture and modeling of these systems.
As a Machine Learning ASIC Engineer, you'll be responsible for developing Data Center Machine Learning ASIC architecture, creating algorithms and models, and building necessary tools. Your work will involve analyzing and mapping data center workloads to ASIC architecture, as well as developing performance and functional models for validation.
The ideal candidate should have at least 5 years of experience in silicon architecture, modeling, or related fields, with strong programming skills in languages like C, C++, and Python. A bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field is required, while a Master's or PhD is preferred.
This role offers competitive compensation ranging from $142,000 to $203,000 per year, plus bonus, equity, and benefits. You'll be working at Meta's facilities in the San Francisco Bay Area, contributing to the company's mission of building technologies that help people connect and grow businesses.
Join Meta's Infrastructure team to work on innovative solutions that push the boundaries of machine learning hardware acceleration while contributing to more efficient and sustainable data center operations. This is an excellent opportunity for someone passionate about the intersection of machine learning and hardware architecture to make a significant impact on Meta's infrastructure.