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 Machine Learning Engineer on the AI Models team at Tenstorrent, you’ll bring up and optimize cutting edge AI models to run on our custom AI devices. You’ll experiment, optimize, and push boundaries while solving real world problems. If you love the craft of ML and want to work on models that are used in real world applications, you’ll feel right at home.

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

Confident with Python programming and hands-on experience with PyTorch for developing deep learning models.
Driven by curiosity and a desire to experiment, always seeking to understand how complex systems work and how to make them better.
Possess a deep understanding of ML model architectures, enabling optimization of both individual components and their interactions.
Easy to work with and excited to collaborate across software and hardware teams.

What We Need

Hands-on experience bringing up state-of-the-art ML models on new hardware platforms.
Strong debugging instincts to investigate performance issues, tune architectures, and boost model accuracy and robustness.
Working knowledge of model optimization techniques—like quantization, sparsity, and attention—as well as hardware features such as matrix engines and memory hierarchies.
A curiosity-driven mindset that stays current with ML research and brings practical insights to real-world engineering challenges.

What You Will Learn

How to get real ML models to fly on a custom AI accelerator.
Ways to optimize ML model performance, from application to silicon level.
What it takes to go from research paper to production ready ML deployment.
How to work alongside compiler, kernel, and hardware teams to drive new features, performance optimizations, and fixes.

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.