Develop high-performance kernels or optimize ML models for Tenstorrent hardware
Work on inference servers, runtime systems, distributed AI coordination, or compiler infrastructure
Build software that manages memory, scheduling, and code execution on specialized hardware
What they're looking for
Currently pursuing BS, MS, or PhD in Computer Science, Engineering, Physics, Math, or related field
Coursework or projects in parallel processing, machine learning, or distributed systems
Experience with C/C++, CUDA, Python, or ML frameworks like PyTorch or TensorFlow
Hands-on experience with model optimization, kernel development, or high-performance programming
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.
This is the team that makes "it runs on Tenstorrent hardware" actually true for real models, at real scale, and builds the infrastructure that keeps the rest of engineering moving fast.
Location: This role is on-site in Toronto, ON.
What you might work on
This posting spans multiple teams within Kernels, Models, Inference, Scaleout & our Runtime teams. One application, one recruiter screen, then we match you to the specific team and location that fits best. Teams include:
Kernels: Develops high performance kernels on Tenstorrent hardware
Models: Optimizes ML models (LLMs, vision models, video and image generation, and other architectures) for our hardware
Inference Server: development and serving-side optimization
Runtime: Builds the software engine that manages memory, task scheduling, and code execution on hardware while an application is actively running.
Scale Out: communication and coordination between devices in a distributed AI system.
Compiler & Infra: Create tools that optimize AI models into high-performance programs on Tenstorrent hardware, covering memory planning, profiling, debug, and emulation.
Who You Are
Currently pursuing a BS, MS, or PhD in Comp Sci, Comp Eng, Physics/Math or a related field.
Coursework or projects any of the following: parallel processing, machine learning or distributed systems.
A high comfort level as an end user of AI and agentic flows.
What We Need
Experience with model quantization, kernel fusion, or other optimization techniques; or low level high performance programming.
Hands on experience working with Pytorch, experimenting with and deploying models, for inference or training.
Experience with C/C++ or kernel development in languages like CUDA, or Python and at least one ML framework (PyTorch, TensorFlow, JAX).
Knowledge of RTL, HDL is nice to have on certain teams.
What You Will Learn
How models get adapted to run well on specialized hardware
How to write high performance code that can get the most out of the underlying hardware
Production ML serving infrastructure at scale
How infrastructure choices affect the velocity of an entire engineering org
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.
From Tenstorrent's public posting, laid out for reading by newgrad.ai with the wording unchanged. Check the original before you apply.
