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

- Experience programming with at least one software programming language

- 3+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience

- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience working with PyTorch or JAX software

- Bachelor's degree in computer science, engineering, mathematics or equivalent, or experience in Java, C++, Python, or a related language

- Experience in debugging, profiling, and implementing software engineering best practices in large-scale systems, or experience in development in the last 3 years

- Strong understanding of computer architecture fundamentals including memory hierarchies (caches, DRAM, HBM), compute pipelines, and interconnect topologies

- Experience applying statistical methods, regression analysis, and data visualization techniques to interpret performance data and drive optimization decisions

PREFERRED QUALIFICATIONS

- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience

- Bachelor's degree in computer science or equivalent

- Experience with machine learning (ML) tools and methods

- 1+ years of continuous integration and continuous delivery (CI/CD), or 1+ years of continuous integration and continuous delivery (CI/CD) experience

- Experience with EDA Simulations or Emulation

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 - 143,700.00 - 194,400.00 USD annually