
Engineer, Software - Fabric
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.
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.
We are looking for a TT-Fabric Software Engineer to help define and build the core networking software that drives our high-performance AI and HPC clusters. In this role, you’ll work close to the metal—designing low-level systems that connect thousands of RISC-V-based and AI processors with speed, scalability, and precision.
This role is hybrid, based out of Warsaw or Gdansk, Poland.
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
- A systems programmer with a strong foundation in C/C++ and a drive to work close to the metal.
- Passionate about networking protocols, bare-metal performance, and distributed communication.
- Curious and analytical — always looking to challenge norms and engineer faster, leaner systems.
- Interested in AI/HPC infrastructure and how low-level software can make or break cluster performance.
What We Need
- Build and maintain TT-Fabric, our custom networking library for AI training and inference.
- Architect communication systems to scale across thousands of AI processors efficiently and reliably.
- Profile, optimize, and tune performance from the protocol level to hardware interfaces.
- Collaborate with hardware and AI teams to integrate TT-Fabric into our distributed runtime.
What You Will Learn
- How to scale custom interconnect software across next-gen RISC-V and AI architectures.
- Techniques to achieve ultra-low latency and high throughput in distributed training clusters.
- Best practices in bare-metal networking, RDMA, and cluster-wide synchronization.
- Cross-disciplinary collaboration between hardware, firmware, and AI research teams.
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.
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