Analog Design Automation Intern
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. At Tenstorrent, die-to-die (D2D) interfaces are how we stitch chiplets together into scalable AI and RISC‑V systems, delivering the bandwidth, latency, and power efficiency our architecture demands. As these links push signaling, process, and packaging limits, we rely on robust analog design automation to explore architectures quickly, verify complex corners, and deliver reliable Silicon at scale. In this role, you will help build and refine automation that our analog designers use every day to design, simulate, and validate D2D PHYs. Your work on flows, scripts, and analysis frameworks will directly impact how fast we can iterate on D2D interfaces, how confidently we can sign them off, and ultimately how Tenstorrent connects and scales its next-generation AI hardware. This role is hybrid based out of Toronto, Boston, Austin or Santa Clara (preferred).
Requirements
- A co-op or PEY student pursuing a BS/MS/PhD in Electrical Engineering with academic exposure to Analog IC design.
- Interest in or academic exposure to Machine Learning concepts (e.g., data analysis, basic model training, optimization).
- Interest in applying Open Source packages and tools to analog design automation problems.
- Strong analytical thinking and communication skills.
Nice To Haves
- A flexible thinker who is excited by the future of AI and eager to work at the boundary between analog circuits and advanced packaging.
- Strong proficiency in Python code conventions
- A curious and motivated student eager to connect the dots between Analog IC design, Data Analytics, and AI/ML tools.
- Interested in how architectural ideas become silicon products and how automation can accelerate the design cycle.
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What This Job Offers
Career Level
Intern
