Meta is seeking an experienced software engineer to join our Accelerator Solutions & Technologies group, supporting the development of Meta's accelerators collective communications software library and optimizing distributed AI/ML workloads' performance. This is an opportunity to work with a engineering team, collaborating with a large set of cross-functional and international partners. Meta's next-generation, super-cluster AI/ML platforms offer the opportunity to work in an fast-paced environment, enabling core technologies deployed in some of the world's largest scale clusters.
Responsibilities
Contribute to our developer infrastructure, including simulation and HW emulation platforms, to enable performance measurement and optimization for Meta's in-house accelerator programs
• Understand and contribute to the collective communications library, intended to be deployed on Meta's AI/ML superclusters
• Support networking and compute hardware acceleration techniques to improve ML inference and training model performance
• Perform architectural analysis to ensure system designs meet performance, scalability, and reliability requirements
• Implement simulation models for Meta's Accelerator ASICs, develop and analyze various scenarios to evaluate data center performance and identify potential improvements
• Collaborate with architects and engineers to integrate simulation results into system design processes
• Use instruction set simulators to define performant firmware for Meta's training/inference accelerators
• Collaborate with hardware and firmware teams to ensure accurate modeling and simulation of accelerator functionalities
• Analyze simulation results to guide firmware development and optimization efforts
Minimum Qualifications
• Currently has, or is in the process of obtaining a PhD degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
• 2+ years experience in developing C++ codebase
• 2+ years experience in developing Python codebase
• Understanding of performance, benchmarking measurement, and optimization on collective communications and distributed at-scale model training
• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
Preferred Qualifications
• Understanding of the transport stack (e.g., RoCE) and its constraints particularly pertaining to interconnect and collective
• Experience with SystemC
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Knowledge of AI/HPC hardware requirements and specifications (e.g., configuring hardware components for AI/HPC workloads)
• Full-stack experience and understanding of AI/HPC systems, with a focus on the application layer and performance optimizations
• Familiarity with relevant tools, libraries, and frameworks (e.g., PyTorch, CUDA)
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
