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 Staff Machine Learning Engineer on the AI Models team at Tenstorrent,
you’ll take the lead in bringing up and optimizing 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.
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, with the ability to
optimize both individual components and overall model performance.
- Comfortable leading a small group of engineers and working closely with
cross-functional 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, flash
attention, kernel fusing, and multi-device parallelization.
- 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.
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.
