AI 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 posting includes 3 unique teams on Tenstorrent's AI software stack - Training, Model and Ops/Kernels. These teams contribute to production software where correctness, scalability, and performance all matter.

This is a full-time, on-site internship for a minimum of 13 weeks; 6 months is preferred. Training and Models teams will be based out of Warsaw. Ops/Kernels team may be based in Gdańsk or Warsaw_._ Final team placements are matched based on candidate skill sets and current team priorities closer to your start date.

What you might work on:

• Training: Develops and profiles distributed LLM training workflows, optimizing training engines, scaling behavior, and diagnostic tools across multi-device systems.
• Models: Optimizes ML models (LLMs, vision models, video and image generation, and other architectures) for our hardware
• Kernels/Ops: Develops high performance kernels on Tenstorrent hardware

Who You Are

• Currently pursuing a BS, MS, or PhD in Computer Science, Computer Engineering, or a related field.
• Comfortable programming in Python and C++, and working in a Linux development environment.
• Grounded in data structures, algorithms, and computer architecture or systems fundamentals.
• Interested in how machine-learning workloads are implemented, measured, and improved on accelerator hardware.
• Curious about performance and comfortable debugging unfamiliar problems across several software layers.

What We Need

• Hands-on coursework, research, or personal projects in machine learning, systems software, or distributed computing.
• Ability to reason about memory layout, parallel execution, communication, and performance tradeoffs.
• Familiarity with a machine-learning framework such as PyTorch, JAX, or TensorFlow.
• Experience using Git, writing tests, and working through unfamiliar technical problems methodically.