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# Post Silicon Engineer (eInfochips)

- **Company:** Arrow Electronics
- **Location:** Cupertino, CA, United States
- **Experience:** Expert
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, Artificial Neural Networks, BIOS, C++ (Programming Language), Cloud Computing, Code Review, Computer Programming, Computer Engineering, Continuous Integration, Software Debugging, Emulators, Firmware, Hardware Interface Design, Python (Programming Language), Linux System Administration, Lua (Scripting Language), Machine Learning, PCI Express, Software Architecture, System Testing, SystemVerilog, Rust (Programming Language), Graphics Processing Unit (GPU), Git, Information Technology, Deployment Automation, AWS Data Analytics, Build Process, Hardware Infrastructure, Software Version Control, Golang
- **Published:** August 1, 2026
- **Apply:** https://www.careerboard.com/us/en/find-jobs-in-United-States/-2BE4C108CB0B0B30F2/

## About the Role

* Strong programming skills (Python, Lua, C/C++, Rust, Go, etc)
 * A solid understanding of computer architecture and chip/system validation methodologies
 * Experience with cloud infrastructure and CI/CD
 * Firmware testing and/or development (BIOS, BMC, drivers)
 * Domain expertise in any of these areas: PCIe, HBM, GPUs, neural networks, ML HW architecture
 * Knowledge of the full validation lifecycle from RTL simulation (SystemVerilog/UVM, VCS, Questa, Xcelium) and emulation (Palladium, Zebu, Veloce) through silicon failure analysis and debug
 * 5+ years of programming with at least one software programming language experience
 * Bachelor's degree or above in computer science, computer engineering, or related field, or Bachelor's degree
 * 5+ years of non-internship system test development, code reviews, source control management, build processes, automated deployments, and operations experience.
 * Experience with Linux environments and Git.
 * Experience with server hardware and debug tools
 * Experience with Machine Learning Hardware/Software Architecture

 * Experience with CI/CD
 * Experience with EDA Simulations or Emulation

Education: Bachelor's degree

Work Arrangement Fully Onsite: Must be able to travel to an Arrow Client office location as requested by Arrow Client leadership.

## Description

As a Senior Validation Engineer on our Machine Learning Acceleration team to work -from early design validation through emulation, silicon bring-up, post-silicon validation, and ongoing support of production systems deployed in AWS data centers. You'll collaborate deeply with architecture, RTL design, design verification, firmware, and software teams to ensure our next-generation AI/ML accelerators meet the highest standards of quality and performance. This role requires bridging multiple domains and broad scope of impact-from low-level hardware interfaces to high-level ML workloads-to deliver exceptional results.

A day in the life

 * Developing comprehensive validation strategies and leads new methodologies to improve validation coverage and time to root cause.
 * Role models detailed test plans covering functional, performance, power, and stress testing from silicon bring-up to product release
 * Mentors and provides direction to junior validation engineers
 * Executes complex test plans from RTL simulation and emulation environments through physical silicon validation
 * Handing complex debug including hands-on silicon bring-up and debug in the lab using oscilloscopes, logic analyzers, and protocol analyzers
 * Validating ML accelerator performance, accuracy, and reliability using real-world neural network workloads
 * Building test infrastructure, CI/CD, and automated regression frameworks to enable efficient validation at scale
 * Collaborating across architecture, design, firmware, and software teams to triage failures and drive root cause analysis to closure
 * Reviewing test results, identifying patterns, and providing feedback to improve design quality and validation coverage

 * Delivering new tests to production systems in AWS data centers and manufacturing to improve fleet health


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