
location_on2110, Griswold Lane, Austin, Travis County, Texas, 78703, United States
Annapurna Labs is a wholly owned subsidiary of AWS, dedicated to developing custom silicon and servers that power the world's largest cloud services provider. As a vertically integrated team, we combine software, firmware, hardware, and silicon design under one roof to build the next generation of cloud infrastructure. Our portfolio includes the Nitro, Graviton, Inferentia, and Trainium families of processors.
The Machine Learning Annapurna organization focuses on Hardware Development, Software Development, Fleet Operations Systems, and Manufacturing, Quality, and Reliability. We are building cutting-edge AI platforms designed to deliver high performance at low cost. Our success relies on delivering world-class server infrastructure capable of handling massive scale and the rapid integration of emergent technologies.
This role sits within the Trainium Manufacturing, Quality and Reliability team, where we lead the manufacturing of AI Servers and Systems based on Trainium chips across cross-geographical Original Design Manufacturers (ODMs) and Contract Manufacturers (CMs). We are changing an industry, and we seek individuals ready to take on this challenge.
As a Senior Manufacturing Engineer, you will serve as the critical interface between our internal system engineering teams and our external ODM and CM partners. You will engage with an experienced, cross-disciplinary staff to conceive and design infrastructure technologies, driving key aspects of product definition, execution, and testing in manufacturing.
In this role, you will be responsible for the full lifecycle of PCBA manufacturing, from design feedback to mass production. You will work closely with internal teams and outside partners to identify and escalate manufacturing challenges early, enforce Design for Manufacturability (DFM) principles, and drive the closure of operational issues during pre-production builds. Your work will directly impact product quality, reliability, throughput, and cost as we ramp up production for our AI accelerators.
We are looking for a responsive, flexible professional who thrives in an open, collaborative peer environment. You must be willing to "roll up your sleeves" to make wide-ranging business decisions and consistently deliver results. This position offers the opportunity to provide technical leadership, mentor engineers, and drive continuous improvement efforts by investigating failures and mitigating root causes.
We value a transparent and efficient hiring process. While specific steps may vary, candidates can generally expect to engage in a series of interviews designed to assess technical depth, problem-solving abilities, and cultural fit. We look for individuals who demonstrate a proven track record of implementing best-in-class test techniques and processes within complex supply chains.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 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 our accommodations page for more information. We will consider for employment qualified applicants with arrest and conviction records in accordance with applicable laws, such as the Los Angeles County Fair Chance Ordinance.
Work model: On-site
2110, Griswold Lane, Austin, Travis County, Texas, 78703, United States
Austin, Texas
Master's degree or equivalent, or experience with DFx (Design for cost, test, manufacturing). Master's degree in Electrical, Mechanical, or Manufacturing Engineering. Expert knowledge of IPC-A-610H, J-STD-001H, IPC-A-600, and IPC-7711/21. Strong experience with SMT lines, including stencil printing, Pick & Place, Reflow, Automated Optical Inspection (AOI), 5DX, and conformal coating/underfill application. Experience with flying probe testing, Design of Experiments (DOE), and root cause analysis tools like 8D or Six Sigma. Familiarity with PLM/PDM systems (Agile, Teamcenter, SAP) and ERP/MES systems.
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Skills: Machine Learning, PCB, Pcba, SMT, Stencil, Spi, Pick-And-Place, Reflow, Aoi, X-Ray.
Education: Bachelor's degree in Mechanical, Electrical, Industrial Engineering, or related STEM field required; Master's degree in Electrical, Mechanical, or Manufacturing Engineering preferred.