Design Quality Engineer in United States

Job Details: Job Description: The Role and Impact As a GPU Platform Hardware Design Engineer, you will play a pivotal role in designing and developing high-quality GPU hardware platforms that drive innovation in high-performance computing, graphics, and visualization technologies. You will lead the design process from initial feasibility studies through board layout, tapeout, and platform power-on, ensuring robust functionality and compatibility with industry standards. Your expertise in platform-level requirements, electrical engineering applications, and system bring-up will directly contribute to delivering cutting-edge GPU systems that accelerate Intel's leadership in computing. Business group The Data Center Group (DCG) is dedicated to advancing Intel's role in powering the digital world with leading-edge technologies. Focused on delivering innovative solutions for data center and cloud environments, DCG supports high-performance computing and graphics to enable capabilities such as AI, machine learning, and advanced visualizations. As part of the GPU IP Engineering team within DCG, you'll contribute to developing GPU systems that meet the evolving demands of the industry while supporting Intel's broader mission to create world-changing technology. Key Responsibilities - Design, develop, and evaluate electronic components, PCBs, and integrated circuits for GPU hardware platforms. - Translate platform-level requirements into detailed specifications and ensure adherence throughout the design process. - Define component placement and trace routing rules to optimize board layouts for performance, power, and signal integrity. - Conduct feasibility studies, board layout, tapeout, and platform power-on activities. - Perform functionality tests and utilize tools to verify platform configurations and compatibility. - Research, develop, and validate firmware, hardwa

We are investing in agentic AI and need a Senior AI Engineer to lead the design and delivery of these systems. This is a foundational hire: you will own both the agent-facing workstreams — pipelines, orchestration, conversational interfaces — and the underlying context layer that makes them reliable, including memory management, knowledge graph integration, and retrieval infrastructure. You will work closely with data engineers, project leads, and client stakeholders, and play a key role in shaping how Lynx builds and ships AI solutions at scale. What This Involves: Lead the architecture and delivery of agentic AI systems end-to-end: agents, orchestration, tool use, and multi-step reasoning workflows. Own the context layer: design and implement memory architectures (episodic, semantic, working memory) and integrate GraphRAG and knowledge graph retrieval into agentic pipelines. Build robust RAG systems — including vector retrieval, graph traversal, and hybrid search — and ensure retrieval quality through evaluation frameworks. Translate client requirements into technical designs, presenting approaches and trade-offs to both technical and non-technical stakeholders. Define standards and reusable patterns for agentic AI development that other engineers at Lynx can build on. Set up observability, evaluation, and monitoring pipelines to ensure AI systems perform correctly in production. Requirements: 5–8 years of software or ML engineering experience, with at least 2–3 years building LLM-based or agentic AI systems in production. Deep hands-on experience with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar) and LLM APIs (OpenAI, Anthropic, etc.). Strong understanding of agent design patterns: ReAct, planning loops, tool use, multi-agent coordination, and memory architectures. Practical experience with GraphRAG or knowledge graph-based retrieval (e.g., Neo4j, Microsoft GraphRAG) and vector databases (Pinecone, Weaviate, Qdrant, etc.). Proficiency in

What you’ll do Partner with medical image reconstruction scientists / engineers to build ML components that improve reconstruction quality, speed, robustness, or quantitative accuracy. Define training/evaluation pipelines, datasets, and metrics that map to user needs and design requirements. Productionize models: inference performance, reproducibility, monitoring for drift/regressions, and safe fallbacks. Collaborate on hybrid algorithms, incorporating physics and learned priors, denoisers, learned regularizers, and quality estimation. Help build tooling for rapid experimentation as well as rigorous verification of algorithm changes. What we’re looking for Strong applied ML experience plus comfort with signal processing / imaging or adjacent domains. Ability to move fluidly between research prototypes and production-quality systems. Strong evaluation discipline: metrics, ablations, data leakage avoidance, and reproducibility. A demonstrated track record of applying ML to physics-based or inverse problems (i.e., shipped projects, a portfolio, or publications.) Useful experience ML for imaging/inverse problems (or adjacent) with strong evaluation discipline and comfort with GPU performance constraints. Pragmatic production mindset: reproducible training/inference, regression testing, and safe deployment in high-stakes contexts. A background in computational physics or scientific computing. Leverage ML-based methods such as PiNNs and Neural Operators to solve partial differential equations arising in ultrasound simulation and imaging. Experience in Agentic-SciML is a plus. Hands-on experience with data curation for ML: building datasets from messy, real-world sources, defining ground truth, and managing labeling or simulation pipelines. Background in data assimilation: combining observations with physics-based models (Kalman filtering, variational methods, ensemble approaches, or learned variants).

Hydraulic Systems Engineer (Associate, Experienced, or Lead) Company: The Boeing Company Boeing Defense, Space & Security (BDS) Mobility, Surveillance and Bombers (MS&B) B-52 Commercial Engine Replacement Program (CERP ) is seeking a Hydraulic Systems Engineer (Associate, Experienced or Senior) to join the Systems Engineering, Integration, and Test (SEIT) team . The selected candidate will drive engineering excellence on this complex development program in Oklahoma City, OK . Position Responsibilities: Operate as the team’s Subject Matter Expert on the B-52 Hydraulics Subsystem. Lead systems and multifunctional engineering efforts for the SEIT IPT, ensuring adherence to technical quality standards throughout the product lifecycle Collaborate with cross-functional teams, including design, manufacturing, and quality assurance, to define and implement systems engineering processes and best practices Conduct trade studies and risk assessments to inform design decisions and optimize system performance, cost, and schedule Develop and maintain system requirements, interface control documents, and verification and validation plans to ensure compliance with customer specifications and regulatory standards Oversee the integration of hardware and software components in System Integration Labs in Oklahoma City Oversee the verification and test of hardware and software components supporting the modification in San Antonio

Associate Manufacturing Engineer Company: The Boeing Company The Boeing Defense, Space & Security (BDS) team is seeking an Associate Manufacturing Engineer for Phantom Works located in Berkeley, MO to support our Specialty Materials Manufacturing portfolio . Who We Are: At Boeing St. Louis, we are leaders in aerospace innovation, dedicated to shaping the future of flight. Our facility serves as a hub for advanced manufacturing, where we design and produce cutting-edge military products that are vital to national defense. We take pride in our commitment to quality, safety, and sustainability. We want you to join our team and contribute to the production of aircraft parts and assemblies made from composite materials. Position Overview: As a Manufacturing Engineer, you will support the development and implementation of production methodologies and tooling for specific materials that are manufactured in St. Louis. You will collaborate with Integrated Product Teams (IPTs) to integrate technical solutions across multiple disciplines, ensuring efficient manufacturing processes that meet stringent quality standards. Position Responsibilities Develop and implement manufacturing processes, plans, and tooling methodologies for specific material fabrication. Collaborate with IPTs to support the integration of technical solutions and ensure manufacturability of material specs. Investigate and resolve technical problems related to material manufacturing processes. Participate in the implementation of Lean principles to enhance operational efficiency and reduce waste. Resolve technical issues that significantly impact performance, cost, or

Work Flexibility: Hybrid The Senior Quality Management System Specialist will help design, maintain, and continuously improve a quality management system that supports regulatory approval and business growth across global markets. You’ll collaborate across functions to ensure quality processes are not only compliant, but practical, efficient, and future‑ready. Activities include Quality System documentation, Internal Quality Agreements, Supplier Quality Agreements, and general QMS activities related to Mergers and Acquisitions. This role is Hybrid in Portage, Michigan . What You Will Do Support and maintain a compliant Quality Management System aligned with global medical device regulations to enable product certification and regulatory clearances. Develop and update quality system processes, procedures, and documentation to reflect business needs and regulatory expectations. Assess and quantify quality system requirements to optimize structure, integration, and scalability. Identify and implement continuous improvement opportunities that increase efficiency and effectiveness of quality processes. Support management review, quality planning forums, and related governance activities with data-driven inputs. Partner with stakeholders to ensure quality processes reflect actual operational activities, including support for new product development. Prepare for and support internal, external, and third‑party quality system audits, including responses and follow‑up actions. Contribute to quality system training content and delivery to ensure effective adoption across the organization. What You Will Need Bachelor’s degree in science, engineering, business, or a related discipline. <

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that deliver the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing some of the world’s most transformative technologies. Our new AI Engineering Campus in Austin will play a central role in building the future of AI computing. The Opportunity We are seeking a system validation engineering intern to help drive server blade and rack validation efforts for next-generation AI infrastructure hardware systems. This role focuses on post-silicon system validation across the full lifecycle of server hardware systems, ensuring functional and performance meets product objectives. You will help drive end-to-end blade and rack validation including development, execution, and debug while collaborating across silicon, firmware, systems, and platform teams. The Blade and Rack Validation team is responsible for ensuring system readiness and quality at scale. The team works cross-functionally with firmware, silicon, and system engineering teams to validate complex AI compute platforms. Type: 12-week summer internship Timing: May - August (exact dates to be confirmed) Commitment: Full-time What You’ll Do Help drive and execute post-silicon validation goals of AI compute blades and racks including testcase planning, development, and automation Help drive validation testcase execution and system debug against program achievements and report validation progress and risks. Drive provisioning and integration of system components (SoC FW, BMC, RMC, OS) for rack-level readiness Triage test failures, collect debug data, and collaborate on root cause analysis. Track validation coverage and continuously improve test processes and infrastructure. What You’ll Bring Working towards a Bachelor's

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary We are seeking an accomplished Principal Cloud Storage Engineer to lead the design, engineering, and evolution of our private cloud storage platforms. This role will focus on large-scale storage architecture, data protection, cyber recovery, and resiliency technologies across complex enterprise environments. The ideal candidate will combine deep technical expertise in storage systems with strong leadership, architectural vision, and the ability to influence technical direction across the organization. Key Responsibilities Architect and engineer enterprise storage platforms that ensure data integrity, availability, security, and disaster recovery readiness Design and implement end-to-end storage solutions, including Software Defined Storage, SAN, NAS, and object storage across private cloud and data center environments Drive strategic technology decisions by evaluating emerging products, tools, and standards supporting storage, data protection, cloud, and compute platforms Lead infrastructure initiatives involving storage modernization, data protection, cyber recovery, data migration, and resilience engineering Develop and execute enterprise strategies for backup, recovery, cyber vaulting, and business continuity Create and maintain comprehensive documentation of storage architectures, configurations, policies, and operation

The DFP Engineer – Manufacturing role defines and implements the validation and screening of new silicon features within high‑volume manufacturing flows. You will translate product requirements into executable test methodologies, infrastructure, and detailed manufacturing test plans that ensure quality, yield, and efficiency at scale. This role sits at the intersection of multiple multi-functional teams to make manufacturing test an outstanding part of the overall codesign and DFP lifecycle. What you will be doing: Own end-to-end manufacturing test methodology across all test stages. Translate system specs and product POR into DFP requirements, test content, coverage, and flows. Define and maintain the DFP roadmap, including infrastructure and turning point planning. Partner multi-functionally to implement test content, debug hooks, and coverage improvements. Drive alignment on manufacturability, test time, binning strategies, and cost vs. coverage trade-offs. Embed testability requirements into design to enable robust screening and debug. Define data and analytics frameworks to support yield analysis and continuous improvement. Lead DFP documentation as the single source of truth and feed findings into future methodologies. What we need to see: MS in Electrical Engineering, Computer Engineering, or related field (or equivalent experience) 6&#43; years in silicon post‑silicon validation and/or high‑volume manufacturing test for complex SoCs, GPUs, CPUs, or similar. Hands‑on experience with test content bring‑up, limit setting, correlation to characterization, and yield/coverage optimization. Proficiency with scripting and data analysis (e.g., Python, MATLAB, R, SQL) for test data analytics, limit tuning, and yield/debug analysis. <

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: The Staff Data Engineer is a senior, hands-on technical contributor within an Enterprise Data domain, owning technical design and the most complex implementation work for assigned data products, capabilities, and integrations. The role establishes, communicates, and evolves the technical approach for the work it leads and is accountable for the quality, durability, and supportability of the solutions it shapes. Staff Data Engineers work directly with business stakeholders to understand needs and shape technical solutions, engaging at a level appropriate to the work they lead. The role is expected to be fluent in both technical execution and business context, translating between them without losing precision in either. The Staff Data Engineer sets technical direction for assigned capabilities and initiatives within the domain, applies enterprise standards and platform patterns, engages Principal Engineers where cross-domain considerations apply, and multiplies the effectiveness of the domain team through design leadership, code review, and mentoring. This role is based in Madison, WI . Essential Duties Include, but are not limited to, the following: Technical design and solutioning Own technical design and hands-on delivery for the most complex or highest-risk work across assigned data products, capabilities, and initiatives, including data models, pipeline architecture, integration patterns, and platform usage decisions. Produce design docume

We are seeking a highly skilled and hard-working Senior Test Developer / test engineer to join our multifaceted Enterprise Software QA team. This role offers an outstanding opportunity to leave your mark on the design, construction, optimization and testing of large-scale infrastructure for various foundational NVIDIA unified cloud services and data center offerings. If you are a dedicated engineer with strong expertise in cloud infrastructure and distributed systems and want to apply your skills with AI tools, this role could fit you perfectly. You will thrive in an exciting, innovative environment. What you'll be doing: Work with development teams on test plans for all layers of SW stack for cloud infrastructure, execution, reviews, failure analysis and assessing overall quality and risk. Work with customer PMs on software issues including technical feedback from OEMs and CSPs. Develop key benchmarks to track execution and deploy process improvements to improve efficiency Leverage AI skills to expedite the test scope, test plan, execution and automation workflows. Lead NVIDIA Cloud and Data Center bring up activities which will involve validation, reporting, working with engineering to debug issues, providing design input at times, adding coverage in different areas. Design, develop and maintain CI/CD pipelines for continuous testing in cloud environments when needed. Perform performance, scalability, and reliability testing of cloud services. Implement and maintain test environments in cloud platforms such as AWS, Azure, or Google Cloud. Supervise the infrastructure to alert on significant events, ensuring the highest level of system performance and reliability. Work with various different partner teams to ensure availability of clusters to test on and take the lead in resolve all issues. Working with tea

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

Manufacturing Test Engineering Manager Position Summary We are seeking an experienced Manufacturing Test Engineering Manager to lead the development and execution of the end-to-end manufacturing test strategy for next-generation AI server platforms and datacenter infrastructure. This role is responsible for defining and driving the manufacturing test architecture from L6 board assembly through L11 rack-level integration and final system validation , ensuring world-class product quality, manufacturability, and production scalability. This leader will manage a team of 3–5 Manufacturing Test Engineers while partnering closely with Hardware, Firmware, Platform, Validation, Quality, Operations, and Joint Design Manufacturing (JDM) partners. The role owns the manufacturing test strategy, test coverage, factory test infrastructure, manufacturing capacity planning, and continuous improvement of manufacturing quality. Key Responsibilities Manufacturing Test Strategy Define and own the end-to-end manufacturing test strategy from L6 board assembly through L11 rack integration . Develop standardized manufacturing test methodologies that optimize quality, throughput, cost of test, and scalability across multiple products and JDM sites. Establish manufacturing test standards, best practices, and engineering processes that support high-volume server manufacturing. Technical Leadership & People Management Lead, mentor, and develop a team of 3–5 Manufacturing Test Engineers supporting multiple hardware programs. Establish team priorities, allocate resources, and ensure successful execution of manufacturing test deliverables. Foster a culture of technical excellence, accountability, collaboration, and continuous improvement. Serve as the primary technical escalation point for manufacturing test and production issues. Cross-Functional Engineering Collaboration Partner with Hardware, Platform, Firmware, Validation, Reliability, Quality, and Operations teams to ensure manufac

About the Team The Systems Integration team is responsible for building the infrastructure, tooling, and validation systems that ensure our device software our device software is reliable, testable, and ready to ship. We design and maintain build systems, CI pipelines, automated test frameworks, and hardware-in-the-loop labs to enable rapid, safe product launches. Our work spans build systems, developer tools, systems integration, and cross-team collaboration to ensure developers can build reliably and ship with confidence. About the Role We are looking for an engineer to help evolve OpenAI’s Consumer Products build and continuous integration systems for a fast-growing engineering organization. This role sits at the intersection of developer productivity, build systems, distributed infrastructure, software quality, and on-device software. You will work on the systems that determine how quickly and confident engineers can move: Bazel-bazed builds, Buildkite pipelines, test coverage, remote caching and execution, CI observability, and tooling that helps engineers understand and fix failures quickly. Our mission is to enable OpenAI to ship software running on consumer devices rapidly with a high bar for correctness, reliability, and safety. The best version of this work is invisible when it succeeds: builds are fast, tests are trusted, CI failures are understandable, and engineers can focus on shipping products instead of fighting infrastructure. This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In This Role, You Will Own and evolve Bazel and yocto-based build and test workflows in a polyrepo environment Design and maintain Starlark rules, macros, toolchains, and integrations that make builds hermetic, reproducible, and easy for teams to adopt Improve CI performance and reliability across Buildkite pipelines, including queue time, build time, cache hit rates, retry b

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary CVS Health is seeking a Principal Software Engineer to lead the design and delivery of enterprise-scale Generative AI solutions that power next-generation healthcare experiences. This role goes beyond hands-on coding—you will define technical strategy, establish architectural standards, and guide multiple teams in building secure, scalable, and cost-effective AI platforms across AWS (Bedrock) and Google Cloud (Vertex AI API). You will partner with product, security, compliance, and enterprise architecture teams to ensure solutions meet business objectives, regulatory requirements, and performance goals. The ideal candidate combines deep technical expertise with leadership skills—capable of influencing cross-org architecture decisions, mentoring engineering teams, and driving responsible AI practices in production. Key Responsibilities Lead end-to-end platform delivery of highly scalable, secure AI services and applications leveraging AWS Bedrock (Foundation Models, Knowledge Bases, Agents, Guardrails) and Google Cloud Vertex AI (Gemini via Vertex AI API, Agent Builder, Vector Search, Search & Grounding) Architect and implement Retrieval-Augmented Generation (RAG) solutions, integrating proprietary data from sources like Amazon S3 and Google Cloud Storage/BigQuery, and using Bedrock Knowledge Bases and/or Vertex AI Search & Groundi