Distributed AI Networking Engineer (TT-Fabric) – Hybrid

Tenstorrent; California (MO); Hybrid; USD 100,000 - 500,000; Full time

Job summary

Tenstorrent is seeking a skilled systems engineer to architect, implement, and maintain TT-Fabric, the low-level networking layer powering distributed AI training and inference.

Hybrid work arrangement available in Santa Clara, CA; Austin, TX; or Toronto, ON, with opportunities to optimize protocols, synchronization, and data movement across thousands of AI processors, collaborating with hardware and software teams.

Qualifications

• Deep C/C++ experience in systems engineering.
• Comfort with low-level or bare-metal environments.
• Strong interest in hardware-software interaction and performance.
• Curiosity about networking and distributed systems at scale.

Responsibilities

• Architect, implement, and maintain TT-Fabric, the low-level networking library for distributed inference and training.
• Design scalable communication systems coordinating thousands of AI processors.
• Optimize protocols, synchronization, and data movement for maximum hardware performance.
• Integrate TT-Fabric APIs with the broader programming model in collaboration with AI and hardware teams.
• Help define the long-term architecture of Tenstorrent’s distributed systems stack.

Skills

Deep C/C++ experience

Low-level/bare-metal

Hardware-software interaction

Distributed systems

Job description

Tenstorrent is seeking a skilled systems engineer to architect, implement, and maintain TT-Fabric, the low-level networking layer powering distributed AI training and inference.

Hybrid work arrangement available in Santa Clara, CA; Austin, TX; or Toronto, ON, with opportunities to optimize protocols, synchronization, and data movement across thousands of AI processors, collaborating with hardware and software teams.