Software Engineer, Systems ML - Frameworks / Compilers / Kernels

Full-time - Mid Level

Lansing, MI

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About the position

In this role, you will be a member of the MTIA (Meta Training & Inference Accelerator) Software team, contributing to the development of a comprehensive AI Compiler strategy within the PyTorch AI framework organization. The position focuses on enhancing the performance and deployment of AI training and inference platforms at Meta by working on core areas such as AI frameworks, compiler stack, and high-performance kernels. You will collaborate with AI researchers and hardware design teams to optimize deep learning models and develop compiler optimizations for next-generation hardware.

Responsibilities

• Development of software stack focusing on AI frameworks, compiler stack, and high-performance kernel development.
• Contribute to the development of PyTorch AI framework core compilers for new AI hardware accelerators.
• Analyze deep learning networks and implement compiler optimization algorithms.
• Collaborate with AI research scientists to accelerate deep learning models in various domains.
• Performance tuning and optimizations of deep learning framework and software components.

Requirements

• Proven C/C++ programming skills.
• Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field, or equivalent practical experience.
• Experience in AI framework development or accelerating deep learning models on hardware architectures.

Nice-to-haves

• A Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field with 12+ years of experience in AI framework development, or a Master's degree with 8+ years, or a PhD with 7+ years of experience.
• Knowledge of GPU, CPU, or AI hardware accelerator architectures.
• Experience with frameworks like PyTorch, Caffe2, TensorFlow, ONNX, TensorRT.
• Experience with CUDA programming, OpenMP/OpenCL programming, or AI hardware accelerator kernel programming.
• Experience with compiler optimizations such as loop optimizations, vectorization, and parallelization.

Benefits

• Bonus
• Equity
• Health benefits