Software Engineer, Systems ML

Meta is hiring a Software Engineer to work on AI infrastructure and intelligent machine learning systems. The role focuses on optimizing ML systems, evaluating approaches, leading cross-team efforts, and improving engineering quality.

Responsibilities:

• 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

Requirements:

• 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
• Master/PhD degree in Computer Science, Computer Engineering
• Technical leadership experience
• Experience with distributed systems or on-device algorithm development
• Experience with recommendation and ranking models
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies