Description
- 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
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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.
USA, CA, Cupertino - 193,300.00 - 261,500.00 USD annually
USA, TX, Austin - 168,100.00 - 227,400.00 USD annually
Annapurna Labs, an AWS organization with development centers in the U.S. and Israel, builds custom silicon and software for AWS customers. Our team combines cloud-scale innovation with world-class expertise across silicon engineering, hardware design, verification, software, and operations to tackle technical challenges that have never been seen before.
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 Senior Validation Engineer on our Machine Learning Acceleration team, you'll lead and 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 and broad scope of impact—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 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
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
- 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
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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, CA, Cupertino - 193,300.00 - 261,500.00 USD annually
USA, TX, Austin - 168,100.00 - 227,400.00 USD annually
Annapurna Labs, an AWS organization with development centers in the U.S. and Israel, builds custom silicon and software for AWS customers. Our team combines cloud-scale innovation with world-class expertise across silicon engineering, hardware design, verification, software, and operations to tackle technical challenges that have never been seen before.
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 Senior Validation Engineer on our Machine Learning Acceleration team, you'll lead and 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 and broad scope of impact—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 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
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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