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Join our Silicon Validation team to validate next-generation machine learning accelerators that power AWS's cloud computing infrastructure. You'll work in a fast-paced, startup-like environment alongside some of the brightest minds in the industry on cutting-edge, internet-scale technology that directly impacts how customers use Machine Learning acceleration. We are changing the landscape of cloud infrastructure by accelerating the development of custom silicon by moving beyond traditional partnerships to dominate in AI training and inference
Your work will span validation of the complete vertical stack—silicon, PCB, high-speed components (HBM, PCIe, chip-to-chip), inter-system connections, and system-to-system interfaces. You'll dive deep into new technology hardware components and scaling technologies that power our Machine Learning boards and servers at scale, ensuring every component of our hardware and software comes together into products our customers rely on.
Key job responsibilities
As a Validation Engineer on our Machine Learning Acceleration team, you'll own critical validation aspects across the entire product development lifecycle—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—from low-level hardware interfaces to high-level ML workloads—to deliver exceptional results.
We are looking for candidates with:
- Strong programming skills (Python, Lua, C/C++, Rust, Go, etc)
- A solid understanding of computer architecture
- Experience with AWS services, cloud infrastructure, firmware development (BIOS, BMC, drivers)
- Validation experience in any of these areas: PCIe, HBM, GPUs, neural networks, ML HW architecture, and/or CI/CD
- Familiarity with the validation lifecycle from RTL simulation (SystemVerilog/UVM, VCS, Questa, Xcelium) and emulation (Palladium, Zebu, Veloce) through silicon failure analysis and debug
A day in the life
- Developing comprehensive validation strategies and detailed test plans covering functional, performance, power, and stress testing from silicon bring-up to product release
- Executing complex test plans from RTL simulation and emulation environments through physical silicon validation
- Conducting 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
- Supporting production systems in AWS data centers and addressing field issues as they arise Basic Qualifications: - Currently has, or is in the process of obtaining a Bachelor’s or Master’s Degree in Computer Science, Computer Engineering, Data Science, Electrical Engineering, or majors relating to these fields
- Strong programming skills in two or more of: C/C++, Rust, Go, Python, Lua
- Familiarity with computer architecture (coursework or projects acceptable)
- Experience with Linux environments and Git
- Experience with system test development, code reviews, source control, build processes, or automated deployments Preferred Qualifications: - Experience with AWS services or cloud infrastructure
- Exposure to firmware development (BIOS, BMC, drivers)
- Validation experience in any of: PCIe, HBM, GPUs, neural networks, ML hardware architecture, and/or CI/CD
- Familiarity with the validation lifecycle — RTL simulation (SystemVerilog/UVM, VCS, Questa, Xcelium), emulation (Palladium, Zebu, Veloce), or silicon failure analysis and debug
- Exposure to Machine Learning hardware or software architecture (coursework or projects acceptable)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, TX, Austin - 110,500.00 - 160,000.00 USD annually
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