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Meta · 3 days ago

Software Engineer, SystemML - Scaling / Performance

Menlo Park, CA

Full-time

Onsite

Mid Level

Meta builds technologies that help people connect, find communities, and grow businesses. In this role, you will be a member of the Network.AI Software team, focusing on enabling reliable and highly scalable distributed ML training on Meta's large-scale GPU training infrastructure with an emphasis on GenAI/LLM scaling.

Computer Software

Comp. & Benefits

Responsibilities

Enabling reliable and highly scalable distributed ML training on Meta's large-scale GPU training infra with a focus on GenAI/LLM scaling

Qualification

Distributed ML TrainingGPU architectureMachine Learning frameworksCUDA programmingNCCLHPCDeep learningPerformance optimizationsData parallel trainingModel parallel trainingAI infrastructureLarge-scale distributed training

Required

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: Distributed ML Training, GPU architecture, ML systems, AI infrastructure, high performance computing, performance optimizations, or Machine Learning frameworks (e.g. PyTorch)

Preferred

Knowledge of GPU architectures and CUDA programming

Experience working with DL frameworks like PyTorch, Caffe2 or TensorFlow

Experience in AI framework and trainer development on accelerating large-scale distributed deep learning models

PhD in Computer Science, Computer Engineering, or relevant technical field

Experience with both data parallel and model parallel training, such as Distributed Data Parallel, Fully Sharded Data Parallel (FSDP), Tensor Parallel, and Pipeline Parallel

Experience in HPC and parallel computing

Knowledge of ML, deep learning and LLM

Experience with NCCL and distributed GPU reliability/performance improvement on RoCE/Infiniband