ML Compiler and Performance Engineer

Meta's Training and Inference Accelerators (MTIA) team is developing novel HW to enable efficient execution of AI training and inference workloads. In this role, you will have end-to-end responsibility for the performance of in-production AI models in their transition from stock HW to MTIA chips, with a focus on models that require multi-node compute. To learn more about MTIA, explore the links below:

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Minimum Qualifications

* Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

* Experience developing and deploying optimizations at the level of PyTorch/Aten or comparable stacks

Preferred Qualifications

* A Masters degree and 4+ years in-domain experience

* A PhD degree and 2+ years in-domain experience

* Experience optimizing multi-node distributed compute

* Experience optimizing runtimes and/or kernels for accelerator platforms

Responsibilities

* Identifying bottlenecks and quantifying opportunities for improving performance

* In-depth, end-to-end performance analysis and reporting

* Developing optimizations to address identified bottlenecks

* Optimizing compute/communication overlap

* Work closely with other compiler teams as well as client teams (Recommendation Systems, Generative AI, etc)

About Meta

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and Whats App further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today-beyond the constraints of screens, the limits of distance, and even the rules of physics.

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