Software Engineer, Systems ML
Meta
- Menlo Park, California, United States
- Menlo Park, California, United States
About
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
- 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 and improve the quality of engineering work in the broader team
- 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 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
- Experience with recommendation and ranking models
- Experience in accelerating deep learning models for large scale distributed Ranking & Recommendation ML systems on AI hardware accelerator architectures and GPUs
- Experience in system performance optimizations such as runtime analysis of latency, memory bandwidth, I/O access, compute utilization analysis and associated tooling development
- Experience working with frameworks like PyTorch, Caffe2, TensorFlow, ONNX, TensorRT
- 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 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
Languages
- English
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