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Job Description: Who You Are

A practical engineer who writes tight, efficient C++ without overcomplicating things.
Curious about how frameworks like PyTorch and TensorFlow work under the hood.
Comfortable getting deep into performance profiling and solving problems on other levels of the stack.
Enjoys working closely with experts across hardware, high performance software, ML and compilers.

What We Need

Experience building tools that help model developers bring up and optimize ML models efficiently.
A background in designing frameworks that support compiler teams targeting PyTorch, JAX, TensorFlow, and other ML stacks.
Strong understanding of software architecture to help shape the core abstractions of the TT-NN library for accelerated ML operations.
A focus on refining APIs and performance to empower researchers developing next-generation ML architectures on Tenstorrent hardware.

What You Will Learn

How high-performance teams work together to enable magic.
Techniques used by hardware designers to optimize data movement and compute.
Advanced compiler strategies from graph transformations to low-level scheduling.
How to scale large models on a new platform built specifically for AI.