Research Scientist, Systems ML - Frameworks / Compilers / Kernels (PhD)
Meta

You will be a member of the Triton Accel team and part of the bigger industry-leading PyTorch AI framework organization. Triton is a breakthrough Python-based language and compiler for authoring performant kernels for AI Accelerators such as GPUs.Our team works on all aspects of Triton - compiler optimizations (architecture-independent and dependent), performance and debug tooling, authoring performant kernels, and more. Our emphasis is OSS, but we also work with internal product teams.

Research Scientist, Systems ML - Frameworks / Compilers / Kernels (PhD) Responsibilities:

• Research and 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 AI Accelerators 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.

Minimum Qualifications:

• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
• Currently has, or is in the process of obtaining, a PhD degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
• Python and C/C++ programming skills.
• Research experience in AI framework development or accelerating deep learning models on hardware architectures, demonstrated through peer-reviewed publications.
• Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment.

Preferred Qualifications:

• Knowledge of GPU, CPU, or AI hardware accelerator architectures.
• Experience working with kernel-writing frameworks like Triton, or CUDA.
• 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.

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