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Senior Yield Enhancement Engineer

Cerebras SystemsCerebras Systems·Semiconductors / AI Hardware

Compensation

$175,000 to $250,000 annually

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Posted

62 days

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About the role

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.

Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.

Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.

The Role: Senior Yield Enhancement Engineer

We are seeking a highly experienced Senior VLSI Product and Test Engineer with 7+ years of relevant experience in Semiconductor Testing/Failure Analysis/Yield Enhancement. The successful candidate will look at ATE datalogs, understand the defects in detail, disposition wafers based on ATE data and drive FA/Yield enhancement using physical/optical inspection techniques used in FA.

Suitable candidate will have depth in testing, characterization of silicon defects, failure modes, and experience delivering end-to-end solutions working closely with teams across chip design, fabrication, validation, production, and manufacturing.

Key Responsibilities

  • Analyze ATE data logs, Shmoo plots, parametric characterization data, and spatial wafer defect patterns.
  • Develop failure analysis tools using optical, photo emission, and laser-based defect localization techniques specific to Cerebras hardware.
  • Develop and execute FIB (Focused Ion Beam) edit plans for Silicon root cause validation.
  • Communicating with OSATs and Fab to drive production testing in HVM environment.
  • Understand DFT strategies including hierarchical scan chains, distributed BIST, SRAM test methodologies, and perform diagnosis on ATE data.
  • Collaborate closely with DFT engineers, silicon architects, designers, performance teams, and software engineers to enhance overall testability and yield
  • Refine test programs across di/dt behavior, voltage-frequency characterization space, current limits, and thermal constraints based on ATE logs and disposition learnings.
  • Understand and write Python scripts and UNIX environment.

Required Skills & Qualifications

  • Bachelor's or Master's degree in Electrical Engineering / Computer Engineering, or related field
  • 7+ years of hands-on experience in semiconductor test engineering/ FA/ Yield Enhancement.
  • Hands-on experience with lab debug tools including Oscilloscopes (high-speed probing and signal integrity), wafer probe stations, probe cards, Keyence/Optical inspection systems, and advanced imaging techniques.
  • Failure analysis (FA) expertise including use of optical probing tools, physical inspection workflows, and correlation of electrical failures to physical defects.
  • Strong capability to read and understand Digital CMOS layouts, power grids, routing structures and SRAM arrays.
  • ATE test program debugging, and yield improvement experience.
  • Good interpersonal skills with the ability and desire to work as a standout colleague and problem solver.
  • Proven track record of working cross-functionally, learning fast, and driving issues to closure
  • Working knowledge of git repositories, GitHub, git actions/Jenkins, merge and release flows to streamline test and release
  • Proficiency in programming languages: Python, C/C++, Perl for large-scale data analysis

Preferred Skills

  • Develop fault isolation techniques using OBIRCH/IREM/LADA optical techniques.
  • Experience with advanced test data analysis tools and machine learning techniques for yield optimization.
  • Familiarity with advanced packaging technologies for wafer-scale systems (TSV, advanced interconnects).
  • Familiarity with in-line testing and diagnostics using CPU memory and execution with self-checking.
  • Knowledge of chip defect profiles and mitigation strategies across manufacturing steps.

Location

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Aplyr's read

Cerebras Systems is at the forefront of AI hardware innovation, attracting top technical talent passionate about pushing the limits of high-performance computing.

Synthesized from recent postings & public sources

What's promising

  • Cerebras Systems develops cutting-edge AI hardware, offering significant advancements in deep learning performance.
  • The company's unique wafer-scale engine technology sets it apart in the semiconductor industry.
  • Cerebras is expanding rapidly, creating diverse opportunities for engineers and technical staff.

What to watch

  • The niche focus on AI hardware may limit broader market opportunities.
  • High competition in AI hardware demands constant innovation to maintain leadership.
  • Limited public information about financial stability and long-term viability.

Why Cerebras Systems

  • Cerebras Systems' wafer-scale engine is the largest chip ever built, revolutionizing AI processing capabilities.
  • The company focuses exclusively on AI and deep learning, offering specialized expertise.
  • Cerebras' technology enables significantly faster AI model training compared to traditional hardware.

Aplyr’s read is generated by AI from public sources. Was it useful?

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About Cerebras Systems

Cerebras Systems is a technology company that specializes in developing high-performance computing solutions, particularly focused on artificial intelligence and deep learning applications.

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