Meta's MTIA Software team is focused on developing and productizing high-performance software and hardware technologies for AI at datacenter scale. The team aims to co-optimize software (algorithms, numerics) and hardware (platform, network) for balanced system design, and invests in optimizing AI production models on existing systems to reduce TCO for key AI services. The role involves developing AI frameworks to accelerate Meta's DL/ML workloads on specialized MTIA AI accelerator hardware.
Requirements
- C/C++ programming skills
- Knowledge of Computer Architecture and Distributed systems with interest in one or more of High Performance Computing, Numerics, Performance and AI hardware including compute, networking and storage
- 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
- 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
- Experience working with frameworks like PyTorch, Caffe2, TensorFlow, ONNX, TensorRT
- Knowledge of GPU, CPU, or AI hardware accelerator architectures
Responsibilities
- Development of Software 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
Other
- Currently has, or is in the process of obtaining, PhD degree in the field of Computer Science or a related STEM field
- Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences
- Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
- Intent to return to degree-program after the completion of the internship/co-op
