Meta is seeking an experienced Machine Learning SOC Engineer to join their engineering team, focusing on runtime and firmware development. This role combines cutting-edge AI technology with systems engineering, offering an opportunity to work on Meta's AI Accelerator technology.
The position involves designing and developing host runtime environments for heterogeneous computing systems, creating device drivers, and implementing APIs and libraries. You'll be working at the intersection of hardware and software, ensuring optimal performance of AI systems while collaborating with both hardware engineers and application developers.
As a Machine Learning SOC Engineer at Meta, you'll be part of a team that's pushing the boundaries of AI technology implementation. The role offers competitive compensation ranging from $142,000 to $203,000 annually, plus additional benefits including bonus and equity packages. Meta's commitment to advancing technology beyond traditional boundaries makes this an exciting opportunity for someone passionate about both machine learning and systems engineering.
The ideal candidate will bring at least 3 years of experience in heterogeneous computing or high-performance computing, along with strong programming skills in languages like C++, Rust, and Python. Knowledge of machine learning frameworks and computer architecture is essential, as is the ability to work effectively in a collaborative environment.
Meta's work environment promotes innovation and professional growth, with opportunities to work on projects that impact billions of users worldwide. The company's focus on moving beyond 2D screens toward immersive experiences like augmented and virtual reality offers exciting challenges and opportunities for professional development.
Located in either Sunnyvale, CA or Austin, TX, this role provides the chance to work with cutting-edge technology while contributing to Meta's mission of connecting people and building communities. The position offers the perfect blend of technical challenge and real-world impact, making it an ideal opportunity for an experienced engineer looking to advance their career in machine learning and systems engineering.