Sr. Manufacturing HW Eng, AI/ML & Storage server development
Team Introduction
AWS Hardware Engineering designs and delivers next-generation cloud infrastructure at global scale. Our Storage & AI/ML Manufacturing team owns the manufacturing engineering lifecycle for custom server platforms — from early design engagement and NPI execution through volume production, supplier quality, and continuous improvement. We partner with ODM/JDM design and manufacturing partners across a global network to deliver hardware at scale with exceptional quality.
We are seeking a Cloud Hardware Development Engineer (Manufacturing) to drive manufacturing excellence across our server portfolio. Depending on the specific role, you will own NPI execution, manufacturing process quality, test and diagnostic development, automation strategy, DFx standards, or reliability engineering — ensuring our platforms launch on time, at quality, and at scale. You will work directly with hardware design teams, ODM/CM partners, and cross-functional stakeholders to close the loop between design intent and manufacturing execution.
What You Will Do
You will own manufacturing engineering for cloud storage server platforms deployed at global scale. Your work spans the full product lifecycle: engaging early with design teams on manufacturability, driving NPI builds through EVT/DVT/PVT at partner sites, building quality systems and test strategies that scale across a multi-ODM network, and continuously improving yield, throughput, and cost. When a new storage platform launches into production, the manufacturing readiness, quality gates, reliability, and process controls are yours. You treat manufacturing risk probabilistically — planning to distributions, not point estimates.
Why You Will Love It
The storage infrastructure you manufacture powers exabytes of customer data across AWS. You will see your process decisions, quality systems, and automation initiatives scale to millions of units across a global manufacturing network. The team is deeply technical, high-trust, and moves fast — you own your domain end to end, from early DFx engagement through production ramp and fleet operations.
The Ideal Candidate
You think across the full manufacturing stack — from PCBA assembly and SMT process control to system-level integration and rack deployment. You are as comfortable on an ODM production floor as you are analyzing yield data or reviewing a DFx scorecard. You drive quality through data and structured problem-solving, not assumption. You hold manufacturing partners to the same standard you hold yourself, and you communicate with clarity across engineering, operations, and leadership. You look for automation and ML-assisted approaches to solve complex issues.
Key job responsibilities
Process Quality & Supplier Management
You start the day analyzing cross-program yield trends, identifying a common failure mode across two verticals that points to a shared component vendor issue. Mid-morning, you facilitate a DFx standards review — updating the NPI playbook with lessons from the latest program launch. In the afternoon, you run a throughput simulation for an upcoming automation investment, building the ROI case for leadership. You end the day reviewing reliability data with the fleet health team, feeding findings back into manufacturing process controls for the current and next-generation platforms. You are willing to travel domestically 4+ times per year. You are willing to travel internationally 2+ times per year.
About the team
The Storage AI/ML Manufacturing team is part of AWS Hardware Engineering — the organization that designs, delivers, and sustains the server and storage hardware behind every AWS service. We own manufacturing engineering for AWS custom storage server platforms, from concept through volume production and fleet-scale operations.
We operate as a Hybrid organization: program-dedicated manufacturing engineers embed in each product vertical for tight NPI alignment, while strategic and portfolio-shared roles centralize under a Manufacturing Lead for cross-program leverage. This structure gives you deep program ownership and broad technical community — whether you sit in a vertical driving a specific product launch or in the central team driving standards, automation, and reliability across the portfolio.
Located in Cupertino / Seattle / Denver, we collaborate with global development teams and ODM partners to deliver storage infrastructure deployed in datacenters worldwide. We move fast with small, empowered teams delivering end to end.
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, WA, Seattle - 159,200.00 - 215,300.00 USD annually
AWS Hardware Engineering designs and delivers next-generation cloud infrastructure at global scale. Our Storage & AI/ML Manufacturing team owns the manufacturing engineering lifecycle for custom server platforms — from early design engagement and NPI execution through volume production, supplier quality, and continuous improvement. We partner with ODM/JDM design and manufacturing partners across a global network to deliver hardware at scale with exceptional quality.
We are seeking a Cloud Hardware Development Engineer (Manufacturing) to drive manufacturing excellence across our server portfolio. Depending on the specific role, you will own NPI execution, manufacturing process quality, test and diagnostic development, automation strategy, DFx standards, or reliability engineering — ensuring our platforms launch on time, at quality, and at scale. You will work directly with hardware design teams, ODM/CM partners, and cross-functional stakeholders to close the loop between design intent and manufacturing execution.
What You Will Do
You will own manufacturing engineering for cloud storage server platforms deployed at global scale. Your work spans the full product lifecycle: engaging early with design teams on manufacturability, driving NPI builds through EVT/DVT/PVT at partner sites, building quality systems and test strategies that scale across a multi-ODM network, and continuously improving yield, throughput, and cost. When a new storage platform launches into production, the manufacturing readiness, quality gates, reliability, and process controls are yours. You treat manufacturing risk probabilistically — planning to distributions, not point estimates.
Why You Will Love It
The storage infrastructure you manufacture powers exabytes of customer data across AWS. You will see your process decisions, quality systems, and automation initiatives scale to millions of units across a global manufacturing network. The team is deeply technical, high-trust, and moves fast — you own your domain end to end, from early DFx engagement through production ramp and fleet operations.
The Ideal Candidate
You think across the full manufacturing stack — from PCBA assembly and SMT process control to system-level integration and rack deployment. You are as comfortable on an ODM production floor as you are analyzing yield data or reviewing a DFx scorecard. You drive quality through data and structured problem-solving, not assumption. You hold manufacturing partners to the same standard you hold yourself, and you communicate with clarity across engineering, operations, and leadership. You look for automation and ML-assisted approaches to solve complex issues.
Key job responsibilities
Process Quality & Supplier Management
- Lead and oversee quality control processes across Contract Manufacturers (CM), Original Design Manufacturers (ODM), and component vendors
- Own PFMEAs, Control Plans, and process flows from NPI startup through end of life
- Drive Root Cause Corrective Action (RCCA) for manufacturing blockers, yield detractors, and quality escapes
- Execute Test Rack Inspections and OK2Ship checklists; issue quality alerts, deviations, and ship-holds as required
- Conduct factory audits and supplier quality assessments across the ODM/vendor network
- Scale up manufacturing processes across a global network ensuring consistent quality and throughput targets
- Design, develop, and maintain manufacturing test software and diagnostic tools deployed at ODM/CM lines
- Debug complex system-level failures at the manufacturing line across compute, storage, networking, power, and thermal domains
- Perform root cause analysis correlating across firmware, kernel, driver, PCIe, signal integrity, and physical layers to isolate faults
- Build automation that reduces manual triage — enabling faster fault isolation and higher first-pass yield
- Develop and optimize system-level test flows (BFT, functional test, stress test, burn-in) for storage server platforms
- Analyze test data and yield trends to identify systemic issues; drive design and process improvements
- Own automation strategy, equipment selection, and ROI justification for manufacturing line automation
- Develop and implement manufacturing test fixtures at the server and rack level
- Define processes around assembly and test fixtures to ensure consistent, repeatable results
- Research and implement automation techniques to improve manufacturing efficiency and reduce human intervention
- Scale up tooling, fixturing, and process across the manufacturing network; standardize across multiple ODM sites
- Build, manage, and deploy CI/CD pipelines for rapid deployment of test code to manufacturing environments
- Lead DFx reviews (DFM/DFA/DFT) leveraging mechanical CAD models, gerber files, and mock-up samples; drive design improvements in partnership with hardware engineering
- Develop and maintain DFx scorecards and NPI playbooks that capture cross-program learnings
- Define manufacturing engineering standards and design best practices adopted across teams and partner organizations
- Drive cross-vertical knowledge reuse — ensuring lessons from one program propagate to others
- Collaborate on manufacturing simulation, digital twin, and throughput modeling initiatives
- Own the interface between design intent and manufacturing execution for DFx requirements
- Own cross-program reliability coverage, matrixed to verticals on demand
- Monitor fleet quality metrics post-launch: server-level annualized failure rates and component-level failure modes
- Correlate component-level failure data with manufacturing lot information to identify systemic issues
- Partner with test and fleet health teams to ensure manufacturing diagnostics align with production monitoring and field failure analysis
- Drive design or process changes for current and future platforms based on operational telemetry
- Perform risk assessment, mitigation, and change management throughout the product lifecycle
You start the day analyzing cross-program yield trends, identifying a common failure mode across two verticals that points to a shared component vendor issue. Mid-morning, you facilitate a DFx standards review — updating the NPI playbook with lessons from the latest program launch. In the afternoon, you run a throughput simulation for an upcoming automation investment, building the ROI case for leadership. You end the day reviewing reliability data with the fleet health team, feeding findings back into manufacturing process controls for the current and next-generation platforms. You are willing to travel domestically 4+ times per year. You are willing to travel internationally 2+ times per year.
About the team
The Storage AI/ML Manufacturing team is part of AWS Hardware Engineering — the organization that designs, delivers, and sustains the server and storage hardware behind every AWS service. We own manufacturing engineering for AWS custom storage server platforms, from concept through volume production and fleet-scale operations.
We operate as a Hybrid organization: program-dedicated manufacturing engineers embed in each product vertical for tight NPI alignment, while strategic and portfolio-shared roles centralize under a Manufacturing Lead for cross-program leverage. This structure gives you deep program ownership and broad technical community — whether you sit in a vertical driving a specific product launch or in the central team driving standards, automation, and reliability across the portfolio.
Located in Cupertino / Seattle / Denver, we collaborate with global development teams and ODM partners to deliver storage infrastructure deployed in datacenters worldwide. We move fast with small, empowered teams delivering end to end.
Basic Qualifications
- Bachelor's degree or above in Electrical or Mechanical Engineering, or Bachelor's degree in Engineering, Mechanical Engineering, Operations, Supply Chain, or Business Administration
- Bachelor's degree in Manufacturing, Chemical, Industrial or Electrical Engineering or a related technical discipline
- 6+ years of manufacturing engineering experience in NPI, process development, or production engineering within semiconductor, server/datacenter hardware, electronics, or high-tech manufacturing
- 3+ years of end-to-end NPI product delivery experience from concept through volume production
- Hands-on experience with SMT assembly processes/PCB fabrication, or industrial automation or robotics
- Strong data analysis skills using statistical tools (JMP, Minitab, Excel, Python) to drive data-driven decisions
- Experience driving quality and schedule execution at multinational JDM, ODM, CM, and supplier partners
Preferred Qualifications
- Master's degree in Manufacturing, Chemical, Mechanical, or Industrial Engineering, or a related field
- 5+ years of relevant industry experience spanning semiconductor equipment, wafer fab operations, advanced packaging, or high-volume server/networking hardware manufacturing
- Experience with Stoarge or GPU-based server or accelerator platform manufacturing
- Experience with PLC programming, industrial controls, and automated test equipment (ATE) in production; ability to troubleshoot PLC-controlled systems and robotic work cells
- Process tool ownership including process-of-record (POR), recipe management, equipment qualification (IQ/OQ/PQ), and OEE tracking for tools such as reflow ovens, pick-and-place, or AOI/AXI
- Experience with DOE (Design of Experiments), MSA (Measurement System Analysis), GR&R studies, and process capability analysis in a production setting
- Track record of driving yield improvement, DFx, PFMEA, and cost optimization through automation and process engineering
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, WA, Seattle - 159,200.00 - 215,300.00 USD annually