About this Software Engineer, TT-Distributed role at Tenstorrent
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.
Who You Are
- 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.
What We Need
- 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.
What You Will Learn
- How large-scale distributed inference and training systems are architected across thousands of accelerators.
- Advanced techniques in collective communication, synchronization, and parallel workload distribution.
- The performance characteristics of Tenstorrent hardware in multi-node cluster environments.
- How distributed programming models integrate with compilers, runtimes, and AI frameworks.
- The real-world challenges of deploying, debugging, and scaling next-generation AI clusters.
Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.
Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.
This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.
