About Etched
Etched is building AI chips that are hard-coded for individual model architectures. Our first product (Sohu) only supports transformers, but has an order of magnitude more throughput and lower latency than a B200. With Etched ASICs, you can build products that would be impossible with GPUs, like real-time video generation models and extremely deep & parallel chain-of-thought reasoning agents.
Job Summary
We are seeking an experienced Product Engineer to lead silicon validation, test program development, and productization for our large-format AI accelerator chips. In this role, you will develop and execute test strategies from first silicon through high-volume manufacturing, partnering with cross-functional teams and external vendors to ensure production quality and cost targets. This role is critical to achieving first-pass silicon success and seamless NPI-to-HVM transitions.
Key Responsibilities
Planning and executing comprehensive silicon characterization from first silicon through production release, including voltage-frequency-temperature characterization, corner testing, guardband determination, and production limit setting
Lead test cost optimization efforts while maintaining quality standards
Architect test flows to balance test time, coverage, and yield learning objectives for complex AI accelerator designs
Drive systematic yield improvement initiatives through data-driven root cause analysis using statistical tools and methods
Establish and track key quality metrics including DPPM and test escapes
Perform die/package level bring-ups, troubleshoot failure modes, and resolve issues by collaborating with design, system validation, and operations teams
Support OSAT bring-up, manage ATE/SLT manufacturing test program releases, and drive toward aggressive test cost goals
Productize test programs and methodologies for seamless transition from engineering to high-volume manufacturing
Analyze field return data and system-level failures to identify test coverage gaps and implement improved screening methods
Drive ATE-system correlation activities to ensure test program accuracy and validate performance against system specs
Manage relationships with test vendors, OSAT partners, and foundry partners
You may be a good fit if you have (must-have/ish)
Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, or related field
5-10+ years of hands-on experience in silicon validation, product engineering, and ATE test development for advanced node semiconductors
Proven track record in yield optimization and DPPM reduction with quantifiable results
Experience with silicon characterization methodologies including Fmax/Vmin characterization and power/thermal validation
High-volume manufacturing test experience with demonstrated production scale results
Proficiency in yield and fail pareto analysis using JMP, Exensio, DataPower, or Optimal Plus
Strong understanding of test program debugging, failure analysis correlation, and yield enhancement techniques
Strong candidates may also have (preferred)
Experience developing and optimizing ATE test programs for wafer sort and final test on Advantest V93K platforms
Experience managing wafer sort and final test across multiple advanced process nodes
GPU, HPC, or AI accelerator chip testing background with production scale results
HBM or high-speed memory interface testing and characterization experience
Leading NPI through high-volume production with multi-vendor qualification across multiple OSAT sites
Driving significant cost reduction initiatives
Multi-site parallel testing strategies and test time optimization for large-format dies
Scripting and automation skills (Python, Perl, TCL) for test data analysis and workflow automation
Cross-functional leadership in silicon bring-up and manufacturing ramp
Benefits
Generous medical, dental, and vision coverage
Housing subsidy of $2,000/month for those living within walking distance of the office
Daily lunch and dinner in our office
Relocation support for those moving to San Jose
How We're Different Etched believes in the Bitter Lesson. We think most of the progress in the AI field has come from using more FLOPs to train and run models, and the best way to get more FLOPs is to build model-specific hardware. We are a fully in-person team in San Jose (Santana Row), and greatly value engineering skills.
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