Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.

As a Principal Software Engineer on the ML Frameworks team at Tenstorrent, you will define and drive the architecture that enables machine learning models to run at breakthrough performance on our custom silicon. You will work across the entire software stack, from compilers to runtime to frameworks like PyTorch, while shaping the abstractions and strategies that unlock the full potential of our hardware. This is a role for someone who thrives on solving difficult performance problems and influencing the direction of AI frameworks at scale.

This role is hybrid, based out of Toronto, ON; Austin, TX; Santa Clara, CA, with the opportunity to be remote on a candidate by candidate basis.

During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Who You Are

A technical leader with deep expertise in C++ and system-level performance, capable of setting direction and mentoring others in writing highly efficient code.
Someone who sees the big picture of ML frameworks, understands how PyTorch, TensorFlow, JAX operate under the hood, and can steer architectural decisions that impact multiple layers of the stack.
Comfortable getting deep into performance profiling and solving problems on other levels of the stack.
Enjoy working closely with experts across hardware, high performance software, ML and compilers.

What We Need

Make it easy for ML engineers and compilers to bringup and optimize new models.
Make it easy for kernel developers to introduce new operations.
Extend and optimize TT-NN to enable lazy evaluation and operation fusion.
Work across all layers with hardware, runtime, compiler, kernels, inference and training teams to know what's possible and what's needed.

What You Will Learn

How ML frameworks and compilers connect at the system level.
How to co-design software frameworks with custom silicon architectures.
How model inference and training work under the hood, from memory layout to operator fusion.
What it takes to build infrastructure that supports fast iteration in research and production.

_Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

__Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

_This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.