Tenstorrent is helping enable a new era in artificial intelligence (AI) and deep learning with its breakthrough processor architecture and software.
The company's mission is to deliver orders of magnitude better performance and efficiency for AI workloads from the datacenter to edge of Cloud by co-designing hardware, software and AI algorithms with our unique technology.
Tenstorrent's architecture scales from datacenter servers to IoT devices with dramatically improved efficiency, flexibility, programmability compared to legacy accelerators including CPUs, GPUs, FPGAs, and TPU-type processors.
It is developed by our world-class team with deep expertise in computer architecture, hardware design and verification, systems engineering, compilers, software development, and machine learning algorithms.
Our engineering-based culture is focused on achieving the highest levels of AI innovation across all of Tenstorrent's technical disciplines.
We constantly strive to blend best-in-class aspects of integrity, openness, diversity and collaboration throughout the company : from the CEO to the engineering leadership and to the newest employee who may be a recent college graduate.
By joining Tenstorrent, you will be an integral part of a highly accomplished and distinguished team that has many years of experience at companies that include AMD, Arm, Intel and NVIDIA, and that thrives on delivering new, innovative products.
Based in Toronto with offices in Austin, Tenstorrent is growing quickly. And, we are proudly backed by top-tier Venture Capital firms including Real Ventures and Eclipse Venture Capital, as well as prominent industry luminaries.
Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.
Tenstorrent is designing machine learning systems which will re-define the state-of-the art for ML processing in many application areas from many chip data center systems to tiny battery powered devices.
As a ML processor bring-up and validation engineer in our System Engineering team, you will have a unique opportunity to work at the intersection of machine learning and systems engineering : performing combined tuning of model + system parameters, studying sparsity and data statistics vs.
power / temperature; debugging performance and power bottlenecks for modern machine learning models. Additionally, the successful candidate will gain experience with state-of-the art ML processor architecture, embedded firmware development, FPGA and board design and debug.