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

Meta is seeking an experienced AI Software Engineer to join their Research & Development teams, focusing on Systems ML and SW/HW co-design. This role represents a unique opportunity to work at the intersection of machine learning infrastructure and hardware optimization at one of the world's leading technology companies.

The position involves applying cutting-edge AI infrastructure and hardware acceleration techniques to build and optimize intelligent ML systems that enhance Meta's products and experiences. The ideal candidate will bring specialized experience in areas such as hardware accelerators architecture, GPU architecture, machine learning compilers, or ML systems.

As a Software Engineer in this role, you'll be responsible for driving large-scale efforts across multiple teams, setting strategic goals for project impact, and developing methodologies and benchmarks to evaluate different approaches. You'll apply deep knowledge of ML infrastructure and its interactions with other systems while mentoring other engineers and research scientists.

The role requires a strong technical foundation with at least 7 years of experience (with a Bachelor's degree) or equivalent combination of education and experience. You'll be working with technologies including Python, C/C++, and various ML frameworks like PyTorch, while focusing on performance optimization and hardware acceleration.

Meta offers a competitive compensation package ranging from $70.67/hour to $208,000/year, plus bonus, equity, and comprehensive benefits. You'll be part of a company that's pushing the boundaries of social technology and moving beyond 2D screens toward immersive experiences in augmented and virtual reality.

This is an excellent opportunity for someone who wants to impact the future of AI infrastructure at scale, working on problems that affect billions of users worldwide. The role combines technical leadership, hands-on development, and the chance to mentor others while working on cutting-edge ML systems optimization.