Software Engineer, TT-Distributed

Tenstorrent•Toronto, ON

22h•$100,000 - $500,000•Hybrid

About The Position

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. As our TT-Distributed Software Engineer, you will develop and optimize distributed software systems that power the most efficient and highest-performing AI and HPC clusters. In this role, you'll work on distributed programming across multiple nodes, utilizing systems programming, inter-node communication, and Tenstorrent’s scalable architectures to advance the state-of-the-art distributed inference and training infrastructure. This role is hybrid, based out of Santa Clara, CA; Austin, TX; or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Requirements

Strong C or C++ engineer with solid foundations in systems programming, operating systems, and distributed systems principles.
Enthusiastic about distributed computing, including IPC, socket programming, and cluster resource coordination.
Comfortable reasoning about scalability, fault tolerance, and performance across multi-node environments.
Curious and first-principles thinker who challenges conventional approaches to distributed system design.
Motivated to grow into a deep technical expert in large-scale distributed AI infrastructure.

Responsibilities

Architect, implement, and optimize distributed software systems that coordinate computation and communication across clusters of AI accelerators and CPUs.
Design and build distributed APIs enabling data-parallel and tensor-parallel AI workloads.
Leverage MPI-based technologies and related frameworks to scale programming models across multiple hosts and compute nodes.
Develop robust systems using IPC, inter-node sockets, and distributed communication primitives to ensure reliability and high performance.
Build and maintain testing, debugging, profiling, and monitoring tools for large-scale distributed workloads and collaborate with model and systems teams on cluster bring-up.