Senior Accelerator Engineer, Cloud AI/ML server team
Amazon (AWS)hyperscaler
Cupertino, California, USA · Denver, Colorado, USA · Seattle, Washington, USA · senior · full time
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Hardwaregpu-generic
Infra layerreliability-sregpu-kernels
Role typedatacenter-engineer
Application deadline: Sep 1, 2026
Do you want to become the go-to GPU expert for the world's largest Artificial Intelligence accelerator fleet, and grow that expertise faster than anywhere else in the industry?
This is a role where you will deepen your GPU expertise at a pace and scale that doesn't exist outside of hyperscale cloud, working directly with the industry's leading GPU vendors, analyzing behaviors across hundreds of thousands of accelerators, and defining standards that govern production deployment. If you have started to develop GPU or accelerator depth and want a position where you own the full lifecycle at fleet scale, this is the role!
AWS Hardware Engineering is looking for a Senior Hardware Development Engineer to own the technical roadmap across all AI accelerator platforms in the organization. You will be the single-threaded owner of GPU lifecycle from defining hardware, firmware and diagnostics requirements, qualification through field operations and translating fleet-scale failure data into vendor action.
Key job responsibilities
GPU Component Lifecycle & Strategy
- Own the technical relationship with vendors across all platforms in the portfolio: roadmap alignment, escalations, partnerships.
- Own qualification of new GPU SKUs and baseboard assemblies during NPI bring-up -- define test plans, acceptance criteria, and production readiness gates
- Define and maintain GPU firmware qualification criteria across the org -- pass/fail gates, staged rollout policy, regression detection methodology
- Drive RMA strategy: build failure evidence packages, negotiate acceptance criteria with vendors, manage submission quotas and pipeline velocity
Fleet-Scale Failure Analysis
- Lead root-cause analysis on fleet-wide GPU failure modes (component errors, PCIE interface errors, thermal events, link degradation, manufacturing escapes) using telemetry, event log data, and vendor diagnostics
- Set GPU health standards: define the metrics, thresholds, and alerting that platform teams execute against
- Define GPU fleet health dashboards: identify relevant telemetry, failure rate trends, replacement pipeline status, firmware version distribution, qualification status
Vendor Engagement & Cross-Team Leadership
- Represent the organization in technical discussions with leading vendor’s engineering -- translate fleet-scale patterns into prioritized vendor action items
- Partner with server teams to ensure consistent GPU operational practices; provide expertise without owning their execution
- Present GPU fleet health, replacement pipeline status, and qualification progress to senior leadership (VP-level) regularly
- Mentor engineers on GPU failure analysis methodology
A day in the life
No two weeks look the same. You might be engaging with our GPU vendor's engineering team on future roadmap options and how upcoming architecture changes affect our technical strategy. You might be defining technical requirements to enable AWS to optimize how we deploy and manage GPUs at scale -- translating fleet failure patterns into firmware feature requests. You might be analyzing thermal and error behaviors across tens of thousands of systems to develop predictive models that catch failures before they impact customers. Or you might be building the data package that proves a manufacturing defect to a vendor and recovers millions in component value.
What's consistent: you are the GPU component owner. You see every failure mode, every firmware release, every new SKU qualification. You develop expertise at a rate that isn't possible when you only see one system at a time -- here you see hundreds of thousands, and you use that scale to become the person both AWS and our vendors turn to for answers.
Located in Cupertino, Seattle, or Denver, you work with global hardware teams, vendor engineering, and cross-AWS accelerator initiatives.
About the team
AWS Hardware Engineering designs and delivers next-generation cloud infrastructure -- the servers, accelerators, and storage platforms that power AWS. Our team builds and operates custom AI accelerator systems at global scale, spanning GPU platforms from manufacturing through multi-year fleet operations. We are directly responsible for the most expensive and supply-constrained components in the AWS fleet.
Do you want to become the go-to GPU expert for the world's largest Artificial Intelligence accelerator fleet, and grow that expertise faster than anywhere else in the industry?
This is a role where you will deepen your GPU expertise at a pace and scale that doesn't exist outside of hyperscale cloud, working directly with the industry's leading GPU vendors, analyzing behaviors across hundreds of thousands of accelerators, and defining standards that govern production deployment. If you have started to develop GPU or accelerator depth and want a position where you own the full lifecycle at fleet scale, this is the role!
AWS Hardware Engineering is looking for a Senior Hardware Development Engineer to own the technical roadmap across all AI accelerator platforms in the organization. You will be the single-threaded owner of GPU lifecycle from defining hardware, firmware and diagnostics requirements, qualification through field operations and translating fleet-scale failure data into vendor action.
Key job responsibilities
GPU Component Lifecycle & Strategy
- Own the technical relationship with vendors across all platforms in the portfolio: roadmap alignment, escalations, partnerships.
- Own qualification of new GPU SKUs and baseboard assemblies during NPI bring-up -- define test plans, acceptance criteria, and production readiness gates
- Define and maintain GPU firmware qualification criteria across the org -- pass/fail gates, staged rollout policy, regression detection methodology
- Drive RMA strategy: build failure evidence packages, negotiate acceptance criteria with vendors, manage submission quotas and pipeline velocity
Fleet-Scale Failure Analysis
- Lead root-cause analysis on fleet-wide GPU failure modes (component errors, PCIE interface errors, thermal events, link degradation, manufacturing escapes) using telemetry, event log data, and vendor diagnostics
- Set GPU health standards: define the metrics, thresholds, and alerting that platform teams execute against
- Define GPU fleet health dashboards: identify relevant telemetry, failure rate trends, replacement pipeline status, firmware version distribution, qualification status
Vendor Engagement & Cross-Team Leadership
- Represent the organization in technical discussions with leading vendor’s engineering -- translate fleet-scale patterns into prioritized vendor action items
- Partner with server teams to ensure consistent GPU operational practices; provide expertise without owning their execution
- Present GPU fleet health, replacement pipeline status, and qualification progress to senior leadership (VP-level) regularly
- Mentor engineers on GPU failure analysis methodology
A day in the life
No two weeks look the same. You might be engaging with our GPU vendor's engineering team on future roadmap options and how upcoming architecture changes affect our technical strategy. You might be defining technical requirements to enable AWS to optimize how we deploy and manage GPUs at scale -- translating fleet failure patterns into firmware feature requests. You might be analyzing thermal and error behaviors across tens of thousands of systems to develop predictive models that catch failures before they impact customers. Or you might be building the data package that proves a manufacturing defect to a vendor and recovers millions in component value.
What's consistent: you are the GPU component owner. You see every failure mode, every firmware release, every new SKU qualification. You develop expertise at a rate that isn't possible when you only see one system at a time -- here you see hundreds of thousands, and you use that scale to become the person both AWS and our vendors turn to for answers.
Located in Cupertino, Seattle, or Denver, you work with global hardware teams, vendor engineering, and cross-AWS accelerator initiatives.
About the team
AWS Hardware Engineering designs and delivers next-generation cloud infrastructure -- the servers, accelerators, and storage platforms that power AWS. Our team builds and operates custom AI accelerator systems at global scale, spanning GPU platforms from manufacturing through multi-year fleet operations. We are directly responsible for the most expensive and supply-constrained components in the AWS fleet.
Basic qualifications
- Bachelor's degree in electrical engineering, computer engineering, or equivalent
- Experience in developing functional specifications, design verification plans and functional test procedures
- 7+ years of hardware design and development experience for server, compute, or large-scale infrastructure platforms
- Experience in developing functional specifications, design verification plans and functional test procedures
- 7+ years of hardware design and development experience for server, compute, or large-scale infrastructure platforms
Preferred qualifications
- 7+ years hardware engineering experience
- Direct experience with data center GPUs and associated tooling
- Experience developing or influencing server roadmap
- Track record of influencing vendor engineering priorities through failure evidence
- Familiarity with GPU thermal management, power delivery, and PCIe and interconnect architectures
- Experience with firmware lifecycle management at scale (qualification, staged rollout, regression detection, rollback)
- Comfortable presenting to VP-level audiences
- Experience working horizontally across multiple platform teams without direct authority
- Strong data analysis skills at fleet scale (statistical failure modeling, trend detection, threshold setting)
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 - 183,000.00 - 247,600.00 USD annually
USA, CO, Denver - 159,200.00 - 215,300.00 USD annually
USA, WA, Seattle - 159,200.00 - 215,300.00 USD annually
- Direct experience with data center GPUs and associated tooling
- Experience developing or influencing server roadmap
- Track record of influencing vendor engineering priorities through failure evidence
- Familiarity with GPU thermal management, power delivery, and PCIe and interconnect architectures
- Experience with firmware lifecycle management at scale (qualification, staged rollout, regression detection, rollback)
- Comfortable presenting to VP-level audiences
- Experience working horizontally across multiple platform teams without direct authority
- Strong data analysis skills at fleet scale (statistical failure modeling, trend detection, threshold setting)
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 - 183,000.00 - 247,600.00 USD annually
USA, CO, Denver - 159,200.00 - 215,300.00 USD annually
USA, WA, Seattle - 159,200.00 - 215,300.00 USD annually