Staff Product Development Engineer - ATE Content Developer

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 looking for a Staff Product Development Engineer - ATE Content Developer, who will be focused on core content development for high-performance AI/ML silicon. They will be responsible for developing production test programs on ATE test platforms, translating DFT/ATPG content into optimized ATE solutions, and implementing Streaming Scan Network (SSN) architectures for efficient test data delivery. High level challenges include reducing test cost while maintaining coverage targets, optimizing test time for chiplet and multi-die architectures, and enabling rapid yield learning through robust test methodologies. The work is done collaboratively with a group of highly experienced engineers across DFT, design, product, and manufacturing domains. This role is hybrid, based out of Austin, TX or Santa Clara, CA. 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 An experienced semiconductor test engineer with 7 years and a BS/MS in EE/ECE/CE and a track record testing complex digital devices on advanced nodes. Hands-on with Advantest V93K and/or Teradyne UltraFlex+ platforms, comfortable owning production test programs end‑to‑end. Deeply familiar with DFT/ATPG flows and test architectures: scan chains, MBIST, compression, JTAG/IEEE 1149.1, and common fault models (stuck‑at, transition, path delay, cell‑aware). Proficient in C/C++ or Java, with strong scripting skills in Python, Perl, or TCL to automate flows, pattern handling, and data analysis. Skilled at debugging across ATE hardware, test programs, and silicon, and at using data to drive root‑cause analysis and yield improvement. What We Need Develop and optimize production test programs on Advantest V93K using the SmarTest 8 environment, from bring‑up through high‑volume manufacturing. Translate ATPG patterns (STIL/WGL) into production‑ready test content, balancing test time, coverage, and cost for chiplet and multi‑die AI/ML devices. Implement and debug Streaming Scan Network (SSN) based content for high‑speed scan delivery, ensuring robust and scalable scan test infrastructure. Own test content for scan, BIST, and memory test structures, collaborating with DFT teams on pattern debug, fault diagnosis, and coverage improvement. Support silicon bring‑up and debug in the lab and at manufacturing sites, including correlation, corner characterization, and PVT studies. Build and maintain automation scripts and test methods that improve productivity, repeatability, and quality across the test lifecycle. Document test architectures, flows, and debug procedures so they can be scaled across products, sites, and engineering teams. What You Will Learn How to test and scale cutting‑edge AI/ML silicon with chiplet and multi‑die architectures, including exposure to 2.5D/3D packaging and HBM integration. Deeper expertise in SSN architectures, high‑speed scan delivery, and next‑generation DFT/test methodologies for complex HPC/AI devices. How to drive end‑to‑end yield learning: from ATE data and STDF analytics through to design, DFT, and manufacturing process feedback. How a fast‑growing AI hardware startup coordinates DFT, design, product, and ... (truncated, view full listing at source)