Software Intern

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.

Overview: This is the team that makes "it runs on Tenstorrent hardware" actually true for real models, at real scale, and builds the infrastructure that keeps the rest of engineering moving fast.

Location: This role is on-site in Toronto, ON.

What you might work on: This posting spans multiple teams within Kernels, Models, Inference, Scaleout & our Runtime teams. One application, one recruiter screen,  then we match you to the specific team and location that fits best. Teams include:

• Kernels: Develops high performance kernels on Tenstorrent hardware
• Models: Optimizes ML models (LLMs, vision models, video and image generation, and other architectures) for our hardware
• Inference Server: development and serving-side optimization
• Runtime: Builds the software engine that manages memory, task scheduling, and code execution on hardware while an application is actively running.
• Scale Out: communication and coordination between devices in a distributed AI system.
• Compiler & Infra: Create tools that optimize AI models into high-performance programs on Tenstorrent hardware, covering memory planning, profiling, debug, and emulation.

Who You Are

• Currently pursuing a BS, MS, or PhD in Comp Sci, Comp Eng, Physics/Math or a related field.
• Coursework or projects any of the following: parallel processing, machine learning or  distributed systems.
• A high comfort level as an end user of AI and agentic flows.

What We Need

• Experience with model quantization, kernel fusion, or other optimization techniques; or low level high performance programming.
• Hands on experience working with Pytorch, experimenting with and deploying models, for inference or training.
• Experience with C/C++ or kernel development in languages like CUDA, or Python and at least one ML framework (PyTorch, TensorFlow, JAX).