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 Software Engineer on the ML Frameworks team at Tenstorrent, you’ll help machine learning models run insanely fast on our custom silicon. You’ll work across the stack, from compilers to runtimes to frameworks like PyTorch, unlocking real performance from real models. If you like bending hardware to your will, you’re in the right place.

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.

We welcome candidates at various experience levels for this role. 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 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.

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.

Due to U.S. Export Control laws and regulations, Tenstorrent is required to ensure compliance with licensing regulations when transferring technology to nationals of certain countries that have been licensing conditions set by the U.S. government.

Our engineering positions and certain engineering support positions require access to information, systems, or technologies that are subject to U.S. Export Control laws and regulations, please note that citizenship/permanent residency, asylee and refugee information and/or documentation will be required and considered as Tenstorrent moves through the employment process.

If a U.S. export license is required, employment will not begin until a license with acceptable conditions is granted by the U.S. government. If a U.S. export license with acceptable conditions is not granted by the U.S. government, then the offer of employment will be rescinded.