Job Details: Job Description: The Role and Impact As a Manufacturing Quality and Reliability Engineer, you will play a pivotal role in ensuring the flawless production and reliability of Intel products. You will manage the qualification of manufacturing ramps to high volume, specifying inspection and testing mechanisms, and conducting quality assessments to confirm compliance with industry-leading standards. Through your expertise, you will drive continuous process improvement, proactively address quality challenges, and optimize cost and production scalability, contributing to Intel's commitment to delivering groundbreaking innovation. Business group The Quality Systems Organization within Intel Foundry is dedicated to ensuring the excellence and dependability of Intel's manufacturing operations and processes. This team focuses on developing and implementing robust quality systems, supporting Intel's broader mission to deliver world-class technological solutions to customers. By fostering a culture of proactive improvement, the group plays a critical role in advancing Intel's manufacturing capabilities. Key Responsibilities - Own the qualification of manufacturing ramps to high volume, ensuring products and processes meet quality and reliability standards. - Develop inspection and testing mechanisms and conduct audits to assess compliance with established quality benchmarks. - Lead continuous improvement initiatives to enhance quality systems and foster a culture of proactive quality management. - Manage excursion events, change control processes, and supplier audits while driving supplier performance improvements. - Represent the quality and reliability function in product engineering and development forums, offering recommendations to enhance system, process, and product reliability. - Develop systems for early detection and containment of excursions and con
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Manufacturing Quality And Reliability Engineer Jobs
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Job Details: Job Description: Owns the qualification of manufacturing ramps to high volume, ensuring the quality and reliability of products and processes sustainably meet organizational requirements. Specifies inspection and testing mechanisms, conducts quality assessments and audits, and evaluates materials, processes, and techniques used in production to confirm compliance to quality standards associated with products and production equipment. Owns health and performance indicators for product quality and reliability that drive optimization of cost, ramp, and volume upside efforts. Drives continuous process improvement and proactive quality programs in the factories to develop a quality culture mindset. Represents quality and reliability function in product engineering and product development forums and makes recommendations in design or formulation to improve system and/or process and product reliability. Responsible for excursion management, change control, supplier audit, and driving supplier continuous improvement. Exhibits leadership amidst complex and impactful MRBs. Develops and implements systems and capabilities for early detection and containment of excursions, conducts risk assessments, and dispositions discrepant material. Synthesizes and extracts insights from structured and unstructured data using statistics and machine learning to determine the disposition of products and systems that do not meet required specifications. Responds to customer reported issues related to manufacturing and provides engineering solutions to address customer concerns and improve customer experience. Note: This role requires regular onsite presence to fulfill essential job responsibilities. <p style="text-align:inh
About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for a product manufacturing & quality engineer, who will be responsible for driving technical initiatives related to the manufacturing, quality and reliability of our AI supercomputer hardware systems to ensure product success from concept to launch and through mass production. You’ll have the opportunity to coordinate with functional SMEs and work with a wide range of stakeholders, from design engineering and operations teams, TPMs, external industry vendors and partners to ensure that all products are developed and delivered on time and to the highest quality standards. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees In this role, you will: Own the integrated manufacturing and quality readiness for a product across L6, L10, and L11, with clear gates, milestones, deliverables, owners, and closure criteria. Lead readiness of process flows, tooling, fixtures, assembly operations, test interfaces, and production controls. Review and contribute to work instructions. Translate product requirements into qualification plans, process controls, test requirements and acceptance criteria with design engineering and Area SMEs Coordinate and drive execution of product and process qualification, reliability testing, and validation with the relevant SMEs. Maintain traceable evidence that assigned products and processes meet agreed performance, reliability,
Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron is seeking a highly motivated and experienced Technical Staff Member to join our Quality Engineering team in Boise, ID. Your role will be crucial in ensuring the reliability and quality of wafers shipped from our Boise manufacturing site! Summary The Product Quality and Reliability team ensures Micron delivers high-quality, reliable semiconductor solutions that meet customer expectations and business objectives. The team partners across product engineering, design, technology development, manufacturing, and reliability organizations to identify risks, solve complex technical challenges, and drive continuous improvements in product performance, yield, and customer satisfaction! Position Overview As a Senior Product Quality and Reliability Engineer, you will be a technical leader. You will drive product excellence in quality, dependability, and yield across advanced semiconductor technologies. You will lead complex technical investigations, influence product and technology decisions, and develop innovative approaches that strengthen quality systems and business outcomes. This role provides an opportunity to have broad interpersonal impact through technical leadership, multi-functional teamwork, and strategic problem-solving. Responsibilities Lead complex investigations involving yield excursions, product deviations, and quality issues, driving root cause identification, containment actions, and sustainable corrective solutions Define product quality and reliability moni
Job Details: Job Description: As a Material Analysis (MA) Technician, you will be part of a Technology Development (TD) and High-Volume Manufacturing (HVM) lab responsible for performing material analysis and failure analysis in support of Intel's silicon process development and high-volume production. You will work on developing imaging, composition analysis and sample preparation techniques, and best-known methods (BKMs) to improve lab analysis quality, efficiency and output. You will directly interface with TD and HVM fab customers and quality/reliability engineers to develop solutions to problems by utilizing lab capabilities. The scope may include wafer and unit level, front-end modules and back-end/far back-end modules. Responsibilities may include but not be limited to: • Conducting hands-on analysis by effectively utilizing lab techniques, from sample prep micro-cleaver, ion mill etcher, mechanical polish to SEM/EDX, Dual beam FIB, TEM techniques to characterize Si fabricated structures at nanometer scales and integrated circuit device to improve process, performance and reliability; and to identify physical failure mode toward the root-cause identification. • Conducting hands-on data collection with various lab equipment’s, and assisting engineers to implement materials characterization techniques to determine fundamental thin film material structure/properties and to collaborate with process development engineers across functional areas and organizations to improve process performance and reliability. • Supporting and sustaining lab equipment. Ensuring that lab analytical capabilities needed to support advanced transistor and interconnect technology and/or product development are in place. Cooperating with other lab areas beyond local MA/FA (Failure Analysis) labs to achieve
About the Team OpenAI, in partnership with our capital and technology partners, is building a global network of advanced datacenters to support the most demanding AI workloads. The Infrastructure Quality team ensures that all datacenter systems are manufactured, delivered, and commissioned to the highest standards of quality, reliability, and performance. We work closely with manufacturing partners, general contractors, engineering teams, and operations staff to ensure that every component is delivered ready for installation, startup, and long-term service. Our work spans from vendor qualification through commissioning, ensuring operational readiness across our global portfolio. About the Role We are seeking an experienced Manufacturing Quality Engineer (MQE) to establish, implement, and manage a manufacturing-focused quality program for datacenter infrastructure. This role will be responsible for vendor oversight, quality assurance, process improvement, and issue resolution for all critical systems. You will lead vendor audits, monitor performance metrics, and coordinate corrective actions to ensure predictable delivery schedules, reduced risks, and operational reliability. By partnering with vendors, construction teams, and internal stakeholders, you will help ensure OpenAI’s datacenters are delivered on time and built to the highest operational standards. Travel Domestic and international travel as needed (estimated 40–60%) to manufacturing sites, datacenter locations, and partner facilities. Key Responsibilities Vendor Oversight & Performance Management Conduct manufacturing evaluation, audits, and improve vendor performance across production, inspection, testing, and delivery phases. Develop and track quality metrics to assess manufacturing performance and identify trends. Partner with vendors to refine processes, training, and quality controls to mitigate risks before shipment. Program Development & Execution Develop and maintain a datacenter-focused m
About the Team OpenAI, in partnership with our capital and technology partners, is building a global network of advanced datacenters to support the most demanding AI workloads. The Industrial Compute team ensures that all datacenter systems are manufactured, delivered, and commissioned to the highest standards of quality, reliability, and performance. We work closely with manufacturing partners, engineering teams, and operations staff to ensure that every component is delivered ready for installation, startup, and long-term service. About the Role We are seeking an experienced Quality Engineer (QE) to drive Product and Site Quality initiatives across OpenAI’s infrastructure ecosystem. In this role, you will establish, implement, and manage a comprehensive, quality-focused program across our global supply chain network, ensuring excellence from design through deployment. You will be responsible for end-to-end quality of finished products, as well as maintaining and elevating manufacturing site quality standards. Working cross-functionally with Design (NPI) and Engineering teams, you will help achieve First Pass Yield (FPY), quality, and reliability targets. This includes leading site and fixture validation efforts, driving yield improvement initiatives (Yield Bridge, CPI), and implementing robust corrective and preventive actions (CAPA) to resolve issues at their root cause. In addition, you will play a key role in supplier quality management, assessing and qualifying new vendors, overseeing ongoing supplier performance, and ensuring readiness for future business awards. You will lead vendor audits, monitor key performance metrics, and coordinate corrective actions to ensure predictable delivery schedules, reduced operational risk, and high system reliability. By partnering closely with external suppliers and internal Engineering and Operations stakeholders, you will help ensure OpenAI’s datacenter infrastructure is delivered on time, meets the highest quality standa
About the Team OpenAI, in partnership with our capital and technology partners, is building a global network of advanced datacenters to support the most demanding AI workloads. The Industrial Compute team ensures that all datacenter systems are manufactured, delivered, and commissioned to the highest standards of quality, reliability, and performance. We work closely with manufacturing partners, engineering teams, and operations staff to ensure that every component is delivered ready for installation, startup, and long-term service. About the Role We are seeking an experienced Quality Engineer (QE) to drive Product and Site Quality initiatives across OpenAI’s infrastructure ecosystem. In this role, you will establish, implement, and manage a comprehensive, quality-focused program across our global supply chain network, ensuring excellence from design through deployment. You will be responsible for end-to-end quality of finished products, as well as maintaining and elevating manufacturing site quality standards. Working cross-functionally with Design (NPI) and Engineering teams, you will help achieve First Pass Yield (FPY), quality, and reliability targets. This includes leading site and fixture validation efforts, driving yield improvement initiatives (Yield Bridge, CPI), and implementing robust corrective and preventive actions (CAPA) to resolve issues at their root cause. In addition, you will play a key role in supplier quality management, assessing and qualifying new vendors, overseeing ongoing supplier performance, and ensuring readiness for future business awards. You will lead vendor audits, monitor key performance metrics, and coordinate corrective actions to ensure predictable delivery schedules, reduced operational risk, and high system reliability. By partnering closely with external suppliers and internal Engineering and Operations stakeholders, you will help ensure OpenAI’s datacenter infrastructure is delivered on time, meets the highest quality standa
Job Details: Job Description: Intel's Design Quality and Reliability organization is seeking an AI Platform Engineer to architect and build an enterprise-grade AI platform for mission-critical engineering work. This platform will enable Intel engineers to analyze complex design, qualification, and reliability data; automate engineering workflows; access organizational knowledge; and make faster, evidence-based decisions throughout the product lifecycle. The successful candidate will combine strong software engineering fundamentals with expertise in AI-native and agentic development. They will be highly proficient with Agentic AI coding assistants and able to use these tools responsibly to accelerate architecture, implementation, testing, debugging, and documentation. This role requires close collaboration with Design, Quality and Reliability, Product Engineering, Manufacturing, IT, Information Security, and other Intel stakeholders. Responsibilities 1. Architect and develop Intel's reusable AI platform for Design Quality and Reliability. 2. Build AI agents and workflows for engineering data analysis, qualification planning, risk assessment, knowledge retrieval, reporting, and process automation. 3. Apply Agentic AI coding assistants to accelerate software development while maintaining rigorous engineering review and validation. 4. Integrate AI capabilities with Intel engineering databases, quality-management systems, internal APIs, spreadsheets, documentation repositories, and workflow tools. 5. Develop production-grade backend services, APIs, data pipelines, model gateways, and agent-orchestration components. 6. Establish shared platform capabilities for identity, access control, tool authorization, memory, observability, evaluation, and auditability. 7. Implement human approval, deterministic validation, and rollback controls for consequential engineering actions. 8.
Job Title Design Quality Engineer Job Description Job title: Design Quality Engineer You Role: While positioned within the Business Unit MR, reporting to the Segment OEM & Coils DQE Leader, you will support the Quality, Reliability and Safety of Medical Devices though all lifecycle phases of the medical device. You will contribute to achieve quality objectives as they relate to: Customer Experience, Complaint Rate, and First Past Yield. You will work in an independent Quality & Regulatory organization with key stakeholders during various stages of the design, development and maintenance of the medical device. Representing Design Quality during the execution of new development programs and sustaining activities and interfacing with regulatory affairs Independent oversight of product performance as this relates to Product Quality, Safety and Reliability During (early) Development and Lifecycle Maintenance: Participate in establishing the quality and reliability strategy specific to the product(s) in scope. Involved in quality target setting in Project Charter Act as a product quality lead by defining the activities in the Product Quality Plan to meet product quality targets Contribute to the execution and delivery of results specific to product quality: Review reliability plans , review key quality related requirements , ensure a proper transfer of design specifications to manufacturing and supply chain and service, perform assessment on the design/architecture on suitability for the quality criteria, and review key product related deliverables (Reliability Reports, Reliability modelling for predictive analysis, FMEA’s, Change Point Analysis, etc.) Apply and facilitate Design for Quality & Reliability best practices (FMEAs, ro
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Join Tenstorrent as a Staff Reliability Engineer and help define the reliability strategy behind the next generation of AI computing systems. In this highly visible technical leadership role, you'll drive reliability from architecture through production, partnering across hardware, software, and manufacturing teams to build high-performance AI platforms that set the standard for uptime, durability, and quality. If you're passionate about solving complex engineering challenges and influencing products at scale, you'll have the opportunity to shape technology powering the future of AI. This role is hybrid, based out of Toronto, Canada. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are You've spent 8+ years in reliability engineering, ideally in high-performance computing, AI hardware, or data center systems. You're comfortable with the statistical side of the job, HALT, HASS, ALT, MTBF, Weibull analysis, and FMEA are all familiar territory. You can work through a technical problem in a thermal lab and then explain the risks and trade-offs clearly to leadership. You're good at bringing people together, mechanical, electrical, thermal, softw
ABOUT THE ROLE As our Senior Engineer, Dimensional Engineering and Metrology, you are the architect of Peloton’s global measurement standards. You will lead a world-class metrology lab and serve as the global Subject Matter Expert (SME) for GD&T, ensuring that our design intent translates perfectly into manufacturing reality. This is a high-visibility role where you will bridge Hardware Engineering and Quality, driving long-term product quality and reliability through advanced statistical analysis and a "zero-error" philosophy. YOUR DAILY IMPACT AT PELOTON Own the Metrology Lab roadmap, including CapEx planning, managing operational infrastructure, and optimizing global measurement processes Define corporate standards for GD&T (ISO/ASME). You’ll lead cross-functional reviews to transition the team from basic dimensioning to data-driven functional gauging and advanced 1D/2D/3D tolerance stack-up analysis Establish measurement correlation protocols and conduct technical audits with overseas partners (JDM/CM), specifically in Asia, to ensure lab-to-factory data alignment and GRS&R capability Oversee high-precision inspections (CNC-CMM, 3D scanning) and lead dimensional root-cause investigations on prototypes to resolve field failures and improve NPI success Partner with Supplier Quality and Hardware teams to integrate Design for Inspection (DFI) principles, validating functional gauges and fixtures before tooling kick-off Act as a mentor and educator, developing technical training programs to elevate metrology literacy and GD&T expertise across the global organization YOU BRING TO PELOTON 10+ years in Dimensional Engineering/Metrology with 3+ years in a technical lead role BS in Mechanical Engineering (MS preferred). GD&T certification (ISO1101 or ASME Y14.5) and Six Sigma Black Belt are significant pluses Expert-level proficiency in PolyWorks, Zeiss Calypso, or PC-DMIS, alongside deep experience in SolidWorks and PTC Windchill Proven success managi
About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Through strategic partnerships and self-built campuses, we are scaling one of the world's fastest-growing AI infrastructure platforms. The Supply Chain organization ensures critical infrastructure components—from compute systems and networking equipment to integrated rack solutions—are sourced, manufactured, qualified, and delivered with the speed and reliability required to support frontier AI development. We partner closely with Hardware Engineering, Manufacturing Quality Engineering, Infrastructure Delivery, Hardware Operations, Finance, and suppliers worldwide to build a resilient, scalable supply chain capable of supporting rapid infrastructure expansion. As Industrial Compute continues to grow, Supply Chain serves as the operational bridge between engineering innovation and large-scale infrastructure deployment. About the Role We are seeking a Supply Chain Manager to lead strategic execution across sourcing, supplier operations, manufacturing quality, and infrastructure delivery for OpenAI's AI infrastructure portfolio. This role will oversee a multidisciplinary team responsible for strategic sourcing, manufacturing quality engineering, and technical program management while partnering closely with engineering, finance, hardware operations, and deployment teams. You will drive supplier strategy, manufacturing readiness, production planning, quality performance, and operational execution across the full hardware lifecycle. Success requires balancing long-term supplier strategy with day-to-day execution. You'll establish scalable operating mechanisms, strengthen supplier partnerships, manage complex cross-functional programs, and ensure OpenAI can rapidly deploy AI infrastructure without compromising quality, cost, or reliability. This is a people leadership role responsible for developing a high-performing organization while driving operati
Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. As an Intern Product Yield Enhancement (PYE) Engineer at Micron Technology Inc., you will assist in taking next generation DRAM devices from design to mass production! PYE Engineers are crucial partners between Research and Development, Manufacturing, Product Engineering and Global Quality teams. Our goal is to offer hands-on and substantial engineering projects that allow interns to gain valuable experience with memory systems and the product life cycle while adding impact to Micron’s business. Our intern programs help prepare engineers for future roles and offer an extraordinary experience that supplements your academic experience! The PYE Engineering role is critical to Micron as it serves the company's charter to be the most cost-effective producer of DRAM memory while delivering the quality and reliability that customers expect from the Micron brand. This position is for a 3-month internship. Responsibilities: Your job duties will include detailed DRAM electrical and physical failure analysis. Identify defects introduced by the semiconductor fabrication process. You will data mine using statistical analysis, AI assisted engineering tools, and automation workflows. Find the root cause of failure mechanisms, communicating results with Management, Product, Process and Test Engineering teams. Complete 3-month internship. Minimum Qualifications: Must be pursuing a minimum of a bachelor’s degree in Electrical Engineering, Computer Engineering,
What we’re doing isn’t easy, but nothing worth doing ever is. Diligent builds helpful robots that work safely and autonomously in real world environments. We move quickly, solve messy problems, and care deeply about reliability at scale. We’re hiring a Manufacturing Reliability Engineer to own production test for our robots at our contract manufacturer: you’ll design and run robust end-to-end test protocols, provision fleets of robots for production, and own the KPIs that define production quality. This role is based in Austin, TX. However, the position will require 50% travel to the Milwaukee, WI area and requires close collaboration across software, hardware, operations, and product engineering teams. Key Responsibilities End-to-end test process ownership. Create, validate, and maintain production test protocols and gating criteria from incoming inspection through final test and shipment. Provisioning of bots. Design and operate provisioning flows (imaging, firmware deployment, configuration, validation) and the tooling/fixtures needed to provision and handoff robots for production. KPIs and continuous improvement. Own key production metrics — First Pass Yield (FPY), cycle time, and test coverage — and drive continuous improvements to meet throughput and quality targets. Test automation & infrastructure. Architect, implement, and maintain automated test frameworks, harnesses, and test rigs used at the CM site. Ensure tests are stable, fast, and provide actionable failure data. Cross-functional escalation & RCA. Lead root-cause analysis for field and production failures; coordinate corrective actions with design, firmware, and CM engineering to close quality loops. On-site production leadership. Be the onsite technical authority at the contract manufacturer: train operators, debug failures on the line, and continuously refine processes with CM partners. What Success Looks Like Improved FPY and reduced rework rates across production builds. Reduced per
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