TT-Fabric Software Engineer

About this role

• Tenstorrent is building the world’s fastest, most efficient AI compute clusters. TT-Fabric is the high-performance nervous system of this platform: the low-level networking layer that lets thousands of RISC-V and AI processors snap together into a single, massively parallel distributed supercomputer
• Architect, implement, and maintain TT-Fabric, our low-level networking library powering distributed inference and training
• Design scalable communication systems capable of coordinating thousands of AI processors efficiently and reliably
• Optimize protocols, synchronization strategies, and data movement to extract maximum hardware performance
• Integrate TT-Fabric APIs into the broader programming model in collaboration with AI and hardware teams
• Help define the long-term architecture of Tenstorrent’s distributed systems stack
• What You Will Learn
• How large-scale AI clusters are architected from the networking layer up
• The performance characteristics of custom AI hardware and RISC-V processors at scale
• Advanced synchronization, collective communication, and interconnect optimization techniques
• How distributed systems design decisions directly influence model throughput and training efficiency
• How hardware and networking software co-evolve in next-generation AI infrastructure- We welcome candidates at various experience levels for this role
• Strong foundation in C/C++, systems programming, or low-level bare-metal programming
• Experience with programming large-scale computer clusters is a plus but not required
• Interest in networking protocols, synchronization and communication in large clusters of computers, and high-performance interconnects
• Experience with high-performance networking libraries, RDMA, or MPI is a plus but not required
• Willingness to think from first principles, consider out-of-the-box solutions, discover where industry norms and current state-of-the-art fall short, and drive to surpass them
• Passion for the intricacies of low-l...