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Sr. Manufacturing Engineer, Design for Manufacturability & Automation, Annapurna AI Systems Manufacturing, Quality and Reliability

Amazon.com Inc
  • Austin, TX
    7 days ago

    Job Description

    The Annapurna AI Manufacturing, Quality and Reliability (MQR) team is part of AWS Annapurna Labs, building the AI platforms that power the world"s largest cloud. We take custom silicon from design through high-volume production across multiple ODM and JDM partners in Asia and North America, at a ramp rate and scale that leaves no room to inspect quality in after the fact.

    We are looking a Senior Manufacturing Engineer to own Design for Manufacturability and manufacturing automation across our accelerator card, baseboard, and rack programs. Your job is to move quality upstream: make the design manufacturable before the drawing is released, and make the line capable of building and verifying it without manual intervention.

    You will sit between hardware design, component suppliers, and ODM process engineering. You will review designs for tolerance capability, land pattern and stencil design, connector retention and insertion, part accessibility, handling, and serviceability - and you will hold the line when a design is not buildable at the yield and rate the program requires. You will then own the automation and metrology strategy that makes the resulting process observable: automated inspection, in-line measurement, fixture design, and the data capture behind it.

    Key job responsibilities

    Design for Manufacturability

    • Own DFM, DFA, and DFT review as a gate prior to drawing release and prior to NPI build, across accelerator cards, baseboards, power distribution, interconnect, and rack-level assembly.
    • Perform tolerance stack-up and GD&T analysis, and establish tolerances that a partner factory can hold at Cpk 1.33 at volume - not tolerances that are theoretically correct and practically unachievable.
    • Reconcile component supplier specifications against AWS drawings before release, and resolve conflicts where a supplier"s requirement is tighter than the drawing allows.
    • Design process margin into the product: solder paste volume against land pattern and via structure, insertion force windows, retention features, and clearance for automated handling.
    • Provide design feedback on connector retention, contact-level defect modes, fastener and cable access, and serviceability in the rack.
    • Build and maintain a versioned DFM design-rule set that carries across product generations, so each program does not relearn the same lessons.

    Manufacturing Automation and Metrology

    • Own the automated inspection and in-line measurement strategy - SPI, AOI, AXI, ICT, vision, and dimensional or true-position measurement - including whether each system is capable of detecting the defect it is deployed against.
    • Drive measurement system analysis across partners: gauge design, gauge R&R, correlation between AWS and supplier measurement, and elimination of methodology differences that make cross-site data non-comparable.
    • Specify and deploy automation that removes manual handling and manual data collection from the line, and automate the capture of measurement and process data into SPC.
    • Own test fixture and tooling design, calibration, and health management, including detection of fixtures that induce false failures.
    • Assess new ODM lines and new sites for process capability before qualification, and define the equipment and process requirements to close gaps.

    Program and Partner Execution

    • Partner with hardware and silicon design teams during development to influence the design while influence is still cheap.
    • Work directly with ODM and JDM process engineering at multiple sites to implement process changes, and verify in production that they held.
    • Drive design and process changes through DCN and ECN, including propagation across all build sites.
    • Build mechanisms - control plans, capability studies, design-rule checks, runbooks - that continue to work at sites you are not present at.

    About the team

    Annapurna Labs is a wholly owned subsidiary of AWS, focused on developing custom silicon and servers including the Nitro, Graviton, Inferentia, and Trainium families of processors. Machine Learning Annapurna (MLA) functions as a vertically integrated team including software, firmware, hardware, and silicon design in a single organization. We are the Annapurna AI Servers and Systems organization under MLA, focused on Hardware Development, Software Development, Fleet Ops Systems, and Manufacturing, Quality, and Reliability. This position is in the Manufacturing, Quality and Reliability team.

    Numbers & Facts

    LocationAustin, TX
    IndustryRetail
    Company Size10,000 employees or more
    Year Founded1994
    Websitehttp://Amazon.com/militaryroles

    About Company

    At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

    Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

    It’s Always Day 1
    At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

    Our Leadership Principles
    Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

    Skills

    • Amazon Web Services (AWS)unmatched
    • Artificial Intelligence (AI)unmatched
    • Automationunmatched
    • Calibrationunmatched
    • Cloud Computingunmatched
    • Computer Firmwareunmatched
    • Computer Serversunmatched
    • DFT (Design for Test)unmatched
    • DRC Flowsunmatched
    • Data Collectionunmatched
    • Data Processingunmatched
    • Geometric Dimensioning and Tolerancingunmatched
    • Hardware Componentsunmatched
    • Hardware Designunmatched
    • Hardware Developmentunmatched
    • Machine Learningunmatched
    • Manufacturingunmatched
    • Manufacturing Automationunmatched
    • Manufacturing Designunmatched
    • Manufacturing Engineeringunmatched
    • Manufacturing Systemsunmatched
    • Metrologyunmatched
    • Organizational Development/Managementunmatched
    • Original Design Manufacturer (ODM)unmatched
    • Process Capabilityunmatched
    • Process Engineeringunmatched
    • Process Improvementunmatched
    • Product/Service Launchunmatched
    • Production Volumeunmatched
    • Software Developmentunmatched
    • Solderingunmatched
    • Systems Analysisunmatched
    • Test Toolsunmatched
    • Tolerance Analysisunmatched
    • Vehicle Fleetsunmatched

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