> Markdown version of [/jobs/ext/2419640-senior-accelerator-engineer-cloud-ai-ml-server-team](https://www.wearedevelopers.com/jobs/ext/2419640-senior-accelerator-engineer-cloud-ai-ml-server-team). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Accelerator Engineer, Cloud AI/ML server team - **Company:** Amazon.com, Inc. - **Location:** Seattle, WA, United States - **Experience:** Expert - **Salary:** $183,000.0 - $247,600.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Cloud Computing, Computer Engineering, Data Centers, Event Logging, Firmware, Hardware Design, PCI Express, Network Switches, Graphics Processing Unit (GPU) - **Published:** August 31, 2026 - **Apply:** https://dejobs.org/x/x/9F50CB5D234D41408A50CD0F9EC17497/job/ ## About the Role * 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, * 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) ## Description 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. ## Related Videos - [Seriously gaming your cloud expertise: from cloud tourist to cloud native](https://www.wearedevelopers.com/videos/373-seriously-gaming-your-cloud-expertise-from-cloud-tourist-to-cloud-native) - [The Sustainability Race: AI's Promises, Pitfalls and Potential](https://www.wearedevelopers.com/videos/100155-the-sustainability-race-ai-s-promises-pitfalls-and-potential) - [Playing Pong on a shoulder press machine](https://www.wearedevelopers.com/videos/100140-playing-pong-on-a-shoulder-press-machine) - [AI Factories at Scale](https://www.wearedevelopers.com/videos/1139-ai-factories-at-scale) - [Building the Nervous System of AI - Michael Kagan (NVIDIA)](https://www.wearedevelopers.com/videos/2133-building-the-nervous-system-of-ai-michael-kagan-nvidia) - [Agent Smith Gets Hardware: Autonomous IoT Hacking From Debug Port to Cloud API](https://www.wearedevelopers.com/videos/100258-agent-smith-gets-hardware-autonomous-iot-hacking-from-debug-port-to-cloud-api) ## Related Articles - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)