Meta-posted 6 days ago
Full-time • Mid Level
Menlo Park, CA

Meta is seeking an AI Software Engineer to join our teams. The position will involve taking these skills and applying them to solve for some of the most crucial and exciting problems that exist on the web. We are hiring in multiple locations.

  • 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
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