Silicon Packaging Design Engineer in United States

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology and amazing people. Today, we're harnessing the boundless possibilities of AI to build the next era of computing. An era in which our GPU acts as the brain of computers, robots, and self-driving cars that can understand the world. Accomplishing unprecedented goals calls for imagination, inventiveness, and exceptional talent from around the world. As a NVIDIAN, you'll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work. Join our team and discover how you can build a lasting impact on the world. NVIDIA designs the silicon behind AI, accelerated computing, and graphics. Power and thermal architecture decisions sit behind every watt of performance and every degree of thermal headroom! We are the Silicon Co-Design Group (SCG). We are hiring a Principal Architect to scout the research and industry landscape, identify emerging system-level co-design ideas in power and thermal, and drive them across teams into product differentiation across NVIDIA's roadmap. This role shapes system, platform, and datacenter feature/behavior, and partners with teams across Nvidia. SCG scope spans across architecture, design, software, operations, platforms, and productization. What you'll be doing: Architect next-generation system, platform, and datacenter-level power and thermal co-design solutions. Scan internal research, academia, standards bodies, and silicon, memory, packaging, and platform partners for what is emerging. Build the product differentiation case for each candidate idea, performance, power, reliability, schedule, cost, and brainstorm what is worth pursuing. Lead end-to-end co-design from concept to product. Drive alignment across architecture, VLSI, softw

Job Details: Job Description: As one of the world's largest semiconductor manufacturers, Intel is committed to advancing every aspect of semiconductor technology, from process development and manufacturing to advanced packaging and reliability characterization. Employees within Intel Foundry are part of a global network spanning technology development, manufacturing, assembly, test, and quality organizations across both front-end silicon and advanced packaging facilities. You will join the Foundry Lab Network (FLN), a key organization within Foundry Quality, Reliability, and Labs (FQRL), located at Intel's growing Chandler, Arizona site. This site serves as the technology development hub for Intel's most advanced packaging technologies, including Hybrid Bond Interconnect (HBI), Embedded Multi-die Interconnect Bridge (EMIB-T), glass substrates, Foveros, and future advanced packaging innovations. FLN is actively expanding its laboratory capabilities and capacity to support Intel Foundry's roadmap, enabling faster technology qualification and accelerating development cycles through Quick Turn Monitoring (QTM) solutions that significantly reduce time-to-data. As the Stress Test and Reliability (STaR) Back-End Laboratory Manager, you will play a critical leadership role within FLN. You will partner closely with Packaging Technology Development, Quality and Reliability, and Failure Analysis teams to establish and enhance laboratory capabilities that support qualification and certification of next-generation packaging technologies and products. This position offers a unique combination of people leadership, technical problem solving, and organizational strategy. You will lead a team of 7-10 talented engineers, spearhead cross-functional efforts to resolve complex reliability and technology challenges, drive strong quality and operati

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. Tenstorrent is seeking a highly skilled and experienced Engineer to lead post-silicon power characterization and correlation activities for cutting-edge semiconductor products. In this role, you will be responsible for developing and executing detailed power measurement strategies on silicon, correlating results with pre-silicon models, and driving improvements across power architecture, design, and modeling methodologies. You will serve as a key technical leader, interfacing across design, architecture, validation, and systems teams to ensure silicon meets power and performance specifications under all operating conditions. This role is hybrid, based out of Toronto, ON or Austin, TX or Santa Clara, CA. 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 A Principal-level engineer with 8+ years in silicon power analysis and characterization, and a Master’s or PhD in EE, CE, or related field. Deep understanding of digital and mixed-signal power domains, including DVFS, leakage vs. dynamic power, and power gating. Highly proficient in lab-based power measurement using oscilloscopes, current probes, power analyzers, and SMUs, plus Python/Perl/MATLAB

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. <

As one of the technology industry's most desirable employers, NVIDIA has been redefining accelerated computing, computer graphics and leading the Artificial Intelligence revolution. NVIDIA's innovation is fueled by its great technology—and amazing people. We are seeking a Senior Silicon and System Product Lead to influence, innovate and take our next generation products to the market. As part of the Silicon Solutions Team, we architect and deliver groundbreaking system solutions that integrate all aspects of the system from silicon design, software design to operations and final deployment in multiple market segments that NVIDIA serves. This position offers an unique opportunity to collaborate with multiple organizations in the company and grow your career in a high impact role. We need a passionate, hard-working and creative individual to lead the products all the way from market analysis to delivering the features on the final product. What you'll be doing: Drive product performance and power targets, trade-off features/configurations and provide innovative solutions to complex silicon and system level problems. Evaluate new market segments and use cases; translate market requirements to engineering problem statements and metrics. Innovate Performance, power, yield and quality optimizations and features for the world’s fastest power-shipping products in the GPU and SoC market segments spanning gaming, automotive, datacenter and DL/AI. Develop methodologies and requirements for multi-functional teams to drive silicon and system product features to production. Incorporate productization feedback to improve the next generation. Lead the team for feature requirements and schedule from architecture to silicon phase of projects. Work alongside system architects, designers, marketing teams, chip and board designers, software/firmware engineers, HW/S

The Silicon Co-Design Group (SCG) sits at the crossroads of architecture, design, marketing, operations, and productization. Our work spans early architecture through final product delivery across Datacenter, Gaming, Robotics, Automotive, and Embedded markets. We work closely across functions to deliver chips that change what is possible. System Integration sits at the intersection of all of them. It is the layer where every architecture, design, software, and manufacturing decision meets reality. When something breaks late in a program, it usually breaks here first. We are hiring a Senior Manager to lead this team in the US and partner closely with teams globally. Your work will sit on the critical path of every NVIDIA silicon program, and the bar you set for system integration is the bar we ship to! The two hardest, highest-leverage problems in this seat: Find critical silicon issues earlier — often before software is production-ready. Left-shifting post-silicon coverage is the highest-value thing System Integration can do. Standing up wide-area testing as a repeatable capability is a core part of the role. Keep programs on milestone when upstream dependencies slip. Validation plans collide with reality every program! The team needs new strategies, not just contingency plans, to keep moving when software, firmware, or methodology slip. You will design and run those strategies. What you’ll be doing: Plan and execute post-silicon feature integration, PVT validation, and wide-area testing across NVIDIA’s GPU, SoC, and CPU programs. Build wide-area and in-system test as a repeatable capability that shifts post-silicon coverage left, so issues surface before we are production-ready. Lead resolution of the most complex system-level issues, RMAs, and HW/SW interaction problems with creative workarounds and focused lab experimentation. Deve

NVIDIA has been redefining computer graphics, desktop gaming, and enhanced computing capabilities for more than 25 years. Today, we are tapping into the unlimited potential of AI to define the next era of computing. As a NVIDIAN, you will work on problems that sit at the boundary of architecture, silicon, firmware, software, and production, where strong judgment matters as much as technical depth. We're the Silicon Design for Productization (DFP) Team, within the broader Silicon Co-Design Group, and we turn power and thermal design into executable productization methodology. Power and thermal are among the most complicated problems we work on at NVIDIA because they sit at the intersection of architecture, workload behavior, silicon variation, firmware policy, platform constraints, and product goals. Small decisions here have an outsized impact on performance, efficiency, reliability, bring-up speed, and ultimately what the product can deliver in the field. We define how features move from concepts to bring-up, characterization, validation, and release. In this role, you will help us build that bridge. We're looking for an engineer who reasons from first principles, flourishes with ownership in a fast-paced environment, and uses AI with sound judgment. What you’ll be doing: Lead the effort across multi-functional teams to keep the program’s power and thermal productization strategy clear, executable, and on track. Create methodology and silicon test plan based controller designs and architecture, including characterization process, debug tools, fuse/firmware settings and lab requirements. Drive resolution for challenging silicon issues through structured hypotheses, measurement plans, and root-cause closure. Steward the Power and Thermal playbook when the existing productization methodology

NVIDIA silicon runs the world's AI infrastructure. The frequency it delivers across every voltage, process corner, and workload is not assumed. It is measured, correlated, and validated. This role does that work. The Silicon Co-Design Group is where architecture intent becomes silicon reality. We own the boundary between what was designed and what was built, and we are the team that knows the difference. When a program ships at frequency and at quality, this team is a reason why. You will be the person who follows through between simulation and silicon. When the model is wrong, a frequency corner that doesn't hold, a Vmin that walks, a critical path that timing analysis missed, you find out why, and your data is what the rest of the program acts on. Architecture, design, and product teams do not guess. They use your numbers. The engineers who do this well are rare. They think like circuit designers, work like experimentalists, and reason like data scientists. If that is you, read on. What you'll be doing: Own silicon speed characterization from first power-on through production sign-off, covering frequency, Vmin, Vmax, and timing margins across the full PVT space. Close the correlation gap. Tie pre-silicon timing analysis and critical path predictions to measured silicon, quantify where the model diverges from reality, and produce analysis that architecture and design can act on with confidence. Trace failures to their source, whether a microarchitectural bottleneck, a critical path that doesn't close under voltage, a clocking issue, or a process corner the model didn't anticipate, and drive the resolution. Own and build AI agents that work at your direction: automated test orchestration, intelligent data pipelines, and analysis flows that expand coverage and compress cycle time without sacrificing difficulty. Know where AI accelerates real work and whe

Graphcore Director-Post Silicon Validation (Functional) Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. We are opening a new AI Engineering Campus in Austin, Texas which will play a central role in Graphcore's work building the future of AI computing. We are developing the next generation of AI compute, a large-scale system-on-chip (SoC) designed to power future high-performance AI systems. Job Summary We have an exciting opportunity to be part of a collaborative, cross-functional development team validating cutting-edge, high-performance AI chips and platforms. You will play a key role in supporting new product introductions and validation. You will lead a team delivering post-silicon validation across the full AI SoC, working across silicon, firmware, and platform levels. The role requires a deep technical understanding, strong hands-on debug experience, and the ability to collaborate effectively with hardware, software, and systems engineering teams. Working within the Validation team, you will be involved with bringing first silicon to life, functionally validating it and working closely with many other teams to help it become a fully characterised and working product, reporting project status/progress to program management on a regular basis. You will have the opportunity to provide technical guidance to other engineering team members. In this role, you can leverage our experience and industry knowledge to architect and drive implementation of continuous improvements to test infrastructure and processes. Th

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions optimized for advanced AI workloads. We collaborate across research, software, and external hardware partners to design and deploy next-generation AI systems at scale. Our team works closely with silicon vendors and system partners to evaluate emerging technologies, validate performance characteristics, and ensure that hardware capabilities translate effectively to real-world AI workloads. About the Role We are seeking a 3P Hardware Architecture Expert with deep expertise in GPU and accelerator architectures to engage directly with silicon vendors and guide hardware decisions for AI infrastructure. In this role, you will evaluate architectural tradeoffs across compute, memory, and interconnect systems, translating vendor specifications into real-world workload impact. You will play a critical role in early silicon evaluation, benchmarking, and performance validation, helping ensure that next-generation hardware meets the needs of our workloads. This role is highly hands-on and requires both deep technical understanding and the ability to engage at a high level with partners such as NVIDIA and AMD on architectural direction and design tradeoffs. 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. Key Responsibilities Engage deeply with silicon vendors (e.g NVIDIA & AMD) on GPU and accelerator architecture tradeoffs. Analyze and interpret performance, power, and efficiency characteristics of next-generation hardware. Translate vendor specifications into expected real-world performance for AI workloads. Evaluate architectural aspects including: compute throughput and utilization memory systems (HBM, cache hierarchies, bandwidth constraints) data types and precision tradeoffs (FP16, BF16, FP8, etc.) interconnect and scaling behavior. Run benchmarks and profiling to validate hardware performance a

NVIDIA's accelerated computing platforms move data at speeds that push the limits of what silicon and physics allow. Whether a high-speed interface trains reliably, maintains accurate margins, and survives every platform topology it will ever see is a question we answer ourselves. This role does that work. The Silicon Co-Design Group leads the boundary between what was designed and what was built. When a GPU, CPU, or SoC ships with interfaces that work at scale, this team is the reason. Most engineers debug within a layer. You will own the full stack. When an interface fails to train, the link margin is unexpectedly tight, or a customer reports a critical silicon issue, you trace the problem through protocol behavior, signal integrity, firmware, platform topology, and silicon marginalities. You then confirm that the fix works. Your methodology shapes how NVIDIA validates high-speed interfaces across generations. Your decisions affect yield, production ramp, and field quality. This is not a coordination role. The engineers who do it well hold protocol depth and system breadth simultaneously, never lose the thread across hardware, firmware, and software, and have the judgment to know when to go deeper and when to act. They are rare. Should that describe you, read on. What you'll be doing: Own post-silicon bring-up, characterization, validation, and debug of PCIe, NVLink, C2C, and other HSIO interfaces across NVIDIA GPUs, CPUs, and SoCs from first power-on through production readiness. Close the hardest failures. Drive root cause across protocol behavior, signal integrity, firmware and driver interactions, platform topology, and silicon marginalities and own every fix through to confirmation. Define validation strategy. Set test coverage, debug priorities, margining methodology, and stress criteria f

About the Role We’re seeking an Associate General Counsel to lead commercial legal strategy and execution for OpenAI’s silicon initiatives and the semiconductor ecosystem that supports our AI infrastructure. This is a senior, highly cross-functional role for a lawyer who can advise business and technical leaders across the semiconductor development, manufacturing, and supply lifecycle. The role will partner closely with silicon engineering, infrastructure, strategic sourcing, supply chain, manufacturing, finance, partnerships, IP, policy, regulatory, and trade compliance teams to structure and negotiate strategic arrangements with semiconductor ecosystem partners, technology providers, and critical suppliers. This person will help establish the commercial frameworks needed to protect OpenAI’s technology and support resilient, scalable commercial arrangements. We’re looking for an experienced technology transactions lawyer with meaningful semiconductor industry experience who can translate highly technical and operational issues into practical commercial structures. The ideal candidate combines strong judgment, commercial creativity, and the ability to lead complex, high-value transactions in a fast-moving and complex global ecosystem. 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. This role will: Lead commercial legal strategy and risk management for OpenAI’s silicon and related technology initiatives. Advise senior business, engineering, sourcing, and operational stakeholders on strategic relationships, commercial priorities, and complex transactions. Draft, negotiate, and advise on sophisticated development, manufacturing, supply, licensing, services, and strategic partnership agreements. Structure commercial arrangements that support long-term business and operational requirements. Advise on the commercial and operational issues that arise across the developmen

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 You will work on the systems software strategy and execution that brings new AI silicon from first power-on to a fully integrated system running production-representative models at expected functionality and performance. You will define how software exercises and validates compute, memory, interconnect, and I/O subsystems, then build the diagnostics, automation, and observability needed to find issues quickly. This role sits at the center of silicon, firmware, platform, systems, and workload teams. You will turn hardware specifications and performance targets into an end-to-end bringup plan, drive cross-functional debug, and establish the stress and regression infrastructure that makes each new platform reliable across operating environments. In this role, you will: Contribute to the end-to-end software bringup and validation strategy for new silicon and first-party systems. Define software-driven test coverage across compute, memory, interconnect, I/O, and their system-level interactions. Build diagnostics, test automation, telemetry, and regression infrastructure that accelerate first-silicon learning and issue isolation. Lead bringup from initial silicon arrival through board and system integration, docking, runtime enablement, and model execution. Design stress tests that characterize reliability, performance, and stability across workloads and operating conditions. Translate architecture specifications and performance models into measurable acceptance crit

Technical Program Manager, Silicon Product Definition — US, CA, Santa Clara. Apply via Workday.

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 software engineer to help build the design methodology, software abstractions, and infrastructure that enable a small silicon team to develop complex chips rapidly and with high confidence. You will turn evolving architecture and design needs into reusable tools and workflows that improve iteration speed, quality, and then apply those tools to help construct world-class silicon. You’ll work closely across architecture, design, verification, performance modeling, and systems software. This role is well suited for an engineer who enjoys building high quality software and is motivated by the challenge of improving velocity and quality of the silicon development process. In this role, you will: Develop and scale design methodologies for rapid first-party chip development and apply them to construct complex custom chips Create abstractions that allow hardware structures, configurations, experiments, and results to be represented consistently across tools. Automate high-value engineering workflows and improve their reproducibility, observability, testability, and ease of use. Partner with architects, RTL designers, verification engineers, compiler engineers, and systems software engineers to gather requirements and then implement solutions. Use methodology and tooling to identify design risks early, accelerate iteration, and improve confidence in performance and implementation tradeoffs. Contribute across multiple aspects of software and hardware