Meta
Software Engineer, Systems ML - Compilers / Kernels
$122K–$181K
Menlo Park, CA +2 · Full-time · Posted Oct 7, 2026
- Location
- Menlo Park, CA
Seattle, WA
New York, NY - Experience
- Bachelor’s degree plus 7+ years, Master’s degree plus 4+ years, or PhD plus 3+ years in AI framework development or accelerating deep learning models on hardware architectures. The posting also lists experience qualifications for AI framework, compiler, and kernel focus areas.
- Education
- Bachelor’s degree in Computer Science, Computer Engineering, or a relevant technical field, or equivalent practical experience; degree must be completed before joining. For the stated experience alternatives: Bachelor’s, Master’s, or PhD in a relevant technical field.
About the job
Develop compiler, framework, runtime, or high-performance kernel software to optimize machine learning training and inference on Meta’s MTIA hardware.
What you'll do
- Develop AI compiler, framework, runtime, or kernel components for current and next-generation hardware.
- Analyze deep learning networks and implement compiler and performance optimizations.
- Collaborate with AI researchers and hardware teams to accelerate models and improve software-hardware performance.
What they ask for
- Proven C/C++ programming skills.
- Experience developing AI frameworks or accelerating deep learning models on hardware architectures.
- Bachelor’s degree in a relevant technical field or equivalent practical experience; the degree must be completed before joining.
- Experience implementing responsible, ethical AI practices.
Nice to have
- Knowledge of GPU, CPU, or AI accelerator architectures.
- Compiler optimization experience; experience with MLIR, LLVM, IREE, XLA, TVM, or Halide is a plus.
Pay
$121,992/year to $181,000/year USD base salary
Tools
C/C++, PyTorch, Caffe2, TensorFlow, ONNX, TensorRT, MLIR, LLVM
AI focus
Build and optimize AI compiler, framework, runtime, and kernel software for deep learning training and inference; work includes accelerating models such as recommendation systems, generative AI, computer vision, and NLP. The posting also calls for responsible AI practices and use of AI tools to improve workflows.
Model-written summary · the original posting is authoritative