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Meta · 2 days ago

Software Engineer, Systems ML - Frameworks / Compilers / Kernels

Menlo Park, CA

Full-time

Onsite

Mid, Senior Level

2+ years exp

Meta builds technologies that help people connect, find communities, and grow businesses. In this role, you will be part of the MTIA Software team, focusing on developing AI compiler strategies and optimizing deep learning models for performance on next-generation hardware. You will collaborate with AI researchers and hardware design teams to enhance the PyTorch AI framework and accelerate machine learning workloads.

Computer Software

Comp. & Benefits

Responsibilities

Development of SW stack with one of the following core focus areas: AI frameworks, compiler stack, high performance kernel development and acceleration onto next generation of hardware architectures

Contribute to the development of the industry-leading PyTorch AI framework core compilers to support new state of the art inference and training AI hardware accelerators and optimize their performance

Analyze deep learning networks, develop & implement compiler optimization algorithms

Collaborating with AI research scientists to accelerate the next generation of deep learning models such as Recommendation systems, Generative AI, Computer vision, NLP etc

Performance tuning and optimizations of deep learning framework & software components

Qualification

C/C++ programmingAI framework developmentCompiler optimizationsGPU architecturesPyTorchCUDA programmingHigh performance kernelsSoft skills

Required

Proven C/C++ programming skills

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

Experience in AI framework development or accelerating deep learning models on hardware architectures

Preferred

A Bachelor's degree in Computer Science, Computer Engineering, relevant technical field and 4+ years of experience in AI framework development or accelerating deep learning models on hardware architectures OR a Master's degree in Computer Science, Computer Engineering, relevant technical field and 2+ years of experience in AI framework development or accelerating deep learning models on hardware architectures OR a PhD in Computer Science Computer Engineering, or relevant technical field

Knowledge of GPU, CPU, or AI hardware accelerator architectures

Experience working with frameworks like PyTorch, Caffe2, TensorFlow, ONNX, TensorRT

OR AI high performance kernels: Experience with CUDA programming, OpenMP / OpenCL programming or AI hardware accelerator kernel programming. Experience in accelerating libraries on AI hardware, similar to cuBLAS, cuDNN, CUTLASS, HIP, ROCm etc

OR AI Compiler: Experience with compiler optimizations such as loop optimizations, vectorization, parallelization, hardware specific optimizations such as SIMD. Experience with MLIR, LLVM, IREE, XLA, TVM, Halide is a plus

OR AI frameworks: Experience in developing training and inference framework components. Experience in system performance optimizations such as runtime analysis of latency, memory bandwidth, I/O access, compute utilization analysis and associated tooling development