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Intel Foundry Ltd Product Yield Engineer in Austin

2 active opportunities · Updated October 2026

Explore current intel foundry ltd product yield engineer jobs in Austin. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 Austin, Texas, United States· Full-time
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

1743 - This position is in Austin, Texas. Position Summary We are seeking an experienced Board-Level Hardware Validation Engineer to define and execute the validation and verification of complex electronic systems throughout the product lifecycle. This role is responsible for defining validation strategies, developing test plans, executing hands-on testing, analyzing failures, and working directly with ODM partners to ensure products meet performance, reliability, quality, and compliance requirements before mass production. The ideal candidate combines strong electrical engineering fundamentals with practical lab expertise and is comfortable personally performing validation activities while coordinating with cross-functional teams and manufacturing partners. Key Responsibilities Validation Strategy & Planning Define comprehensive board-level and inter-board validation plans based on product requirements, design specifications, and customer use cases. Develop validation methodologies covering functional, electrical, thermal, power, signal integrity, reliability, and stress testing. Establish test coverage, acceptance criteria, qualification requirements, and release gates. Review hardware architecture, schematics, component specifications, and interface topologies to identify validation risks early in the design cycle. Define incremental validation and regression coverage for component substitutions, design changes, and firmware updates. Hands-On Validation Execution Develop, automate, and execute validation tests on prototype and production-intent hardware. Perform board bring-up, functional verification, electrical characterization, and system-level integration testing. Validate communication interfaces, control signals, and timing requirements. Verify power sequencing, reset behavior, leakage current, and recovery across operating states. Execute temperature and voltage corner testing against approved operating limits. Use oscilloscopes, logic an

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📍 Austin, Texas, United States· Full-time
✓ High-confidence listing

$100K – $500K/yr

Quick readStrong listing-quality and freshness signals

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. As our TT-Distributed Software Engineer, you will develop and optimize distributed software systems that power the most efficient and highest-performing AI and HPC clusters. In this role, you'll work on distributed programming across multiple nodes, utilizing systems programming, inter-node communication, and Tenstorrent’s scalable architectures to advance the state-of-the-art distributed inference and training infrastructure. This role is hybrid, based out of Santa Clara, CA; Austin, TX; or Toronto, ON. 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 Strong C or C++ engineer with solid foundations in systems programming, operating systems, and distributed systems principles. Enthusiastic about distributed computing, including IPC, socket programming, and cluster resource coordination. Comfortable reasoning about scalability, fault tolerance, and performance across multi-node environments. Curious and first-principles thinker who challenges conventional approaches to distributed system design. Motivated to grow into a deep technical expert in large-scale distributed AI infrastructure. What We Need Architect, implement, and optim

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