Tenstorrent

Develop and optimize low-level acceleration kernels that power high-performance machine learning workloads on Tenstorrent’s AI hardware. This hybrid Toronto role focuses on maximizing compute, memory, and instruction-level efficiency at the software-hardware boundary.

Build and optimize the C++ machine learning training framework powering Tenstorrent’s advanced models on custom AI silicon. This hybrid Poland-based role focuses on high-performance operators, layers, model integration, and hardware-aware performance tuning.

Build TT-Fabric, the low-level networking layer connecting thousands of RISC-V and AI processors into a massively parallel AI supercomputer. This role focuses on high-performance protocols, synchronization, and distributed systems at the hardware-software boundary.

Staff Software Engineer building and operating the platform infrastructure behind Tenstorrent’s high-performance AI cloud across on-premises and public cloud environments. The role combines backend services, infrastructure automation, observability, and site reliability engineering.

Build and optimize distributed software infrastructure powering large-scale AI and HPC clusters across thousands of accelerators. This hybrid role focuses on systems programming, inter-node communication, and high-performance distributed inference and training.

Build and optimize low-level C/C++ systems software that powers Tenstorrent’s high-performance AI processors and distributed accelerator infrastructure. This hybrid Toronto role works closely with hardware, runtime, and model-development teams on performance-critical scale-out systems.

Build and optimize low-level Metal runtime software that powers Tenstorrent’s AI accelerators. This hybrid role focuses on bare-metal execution, scheduling, memory movement, and performance at the hardware/software boundary.

Lead firmware development for microcontrollers and SoCs, building low-level software, bringing up boards, and debugging issues across the hardware–software boundary. This hybrid Toronto role offers broad technical influence across architecture, validation, production, and mentorship.