DFT Design Engineer, Machine Learning Acceleration

Job Title

DFT Design Engineer, Machine Learning Acceleration

Role Summary

Member of the Cloud-Scale Machine Learning Acceleration team responsible for design and optimization of Design-for-Test (DFT) for AWS custom SoCs used in machine learning inference and training servers (Inferentia, Trainium). Focus is on delivering high test coverage, cost-effective test patterns, and supporting silicon bring-up at scale.

Experience Level

Mid-level — role expects experienced engineers. The posting specifies 5+ years of practical DFT experience.

Responsibilities

Primary responsibilities include designing DFT architectures and enabling testability across complex SoC blocks and systems.

• Define and develop DFT architectures for advanced process nodes.
• Collaborate with block designers, RTL teams, and physical design (PD) to implement DFT solutions.
• Perform RTL coding and verification using Verilog/SystemVerilog for DFT insertion and test logic.
• Use industry-standard DFT tools (ATPG, JTAG, MBIST) to generate high-coverage, cost-effective test patterns.
• Develop automation scripts to accelerate DFT flows and test generation.
• Participate in silicon debug with ATE and system teams to diagnose failures and optimize yield.
• Communicate design and test trade-offs across multiple disciplines (PD, DV, ATE, system).

Requirements

Must-have technical skills and experience; preferred items listed separately.

• 5+ years practical DFT experience on complex SoC designs at advanced technology nodes.
• Hands-on experience with ATPG, JTAG, MBIST and making test quality vs. test time trade-offs.
• RTL/SystemVerilog coding and verification experience for DFT-related logic.
• Experience developing automation scripts (e.g., Perl, Python, Tcl).
• Practical experience in silicon debug and collaboration with ATE/system teams.

Nice-to-have:

• Experience developing STA constraints for DFT modes and working with PD to close timing.
• Gate-level simulation setup and SDF-based debug experience.
• Experience with yield optimization techniques.

Education Requirements

Bachelor's degree in Electrical Engineering, Communications Engineering, Computer Engineering, Computer Science, or a related technical field is required. A Master's degree in a related field is preferred. The posting allows related-field alternatives; no specific certifications were listed.

About the Company

Company: Amazon Web Services

Headquarters: Seattle, Washington, USA

Amazon Web Services (AWS) provides a comprehensive and evolving cloud computing platform that includes infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). AWS allows business and developers to use a wide range of cloud services for computing power, storage, and content delivery, among others, thus fostering innovation and enabling faster deployment of applications. AWS is designed to be scalable, flexible, and cost-effective across industries worldwide.