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Meta · 7 hours ago

Software Engineer, Systems ML - Frameworks / Compilers / Kernels

Bellevue, WA

Full-time

Onsite

Mid, Senior Level

4+ 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 a comprehensive AI Compiler strategy and working closely with AI researchers to optimize deep learning models for Meta's hardware.

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 optimizationsCUDA programmingPerformance tuningDeep learning modelsCollaboration skillsProblem-solving skillsCommunication skills

Required

Proven C/C++ programming skills

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

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

Preferred

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

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

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

A Bachelor's degree in Computer Science, Computer Engineering, relevant technical field and 7+ 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 4+ 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 and 3+ years of experience in AI framework development or accelerating deep learning models on hardware architectures

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

Knowledge of GPU, CPU, or AI hardware accelerator architectures