Machine Learning SOC Engineer

Meta is seeking an experienced Machine Learning SOC Engineer to join their Infrastructure Engineering team. This role focuses on runtime and firmware development for AI Accelerator systems. The position combines hardware engineering with software development, requiring expertise in heterogeneous computing systems and runtime environments. The ideal candidate will work on designing and developing host runtime environments, implementing device drivers, and creating APIs for seamless system integration.

The role offers competitive compensation ranging from $142,000 to $203,000 annually, plus bonus and equity opportunities. Based in either Sunnyvale, CA or Austin, TX, this position requires 3+ years of experience in heterogeneous computing or high-performance computing, along with strong programming skills in C++, Rust, and Python.

At Meta, you'll be part of a team that's pushing the boundaries of AI and machine learning infrastructure, working on cutting-edge technology that powers Meta's various platforms and future innovations. The company offers comprehensive benefits including medical, dental, and vision insurance, along with equity opportunities.

This is an excellent opportunity for engineers passionate about machine learning infrastructure who want to work at the intersection of hardware and software, contributing to Meta's next generation of AI acceleration technologies. The role combines technical challenges with collaborative opportunities, working alongside hardware engineers and application developers to optimize performance and solve complex technical problems.