Silicon Packaging Design Engineer in United States

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 As a Hardware Chips Programs Manager at OpenAI, you will help bring our chips hardware roadmap to life, navigating an array of technical and partnership challenges. We’re looking for people excited to push the frontiers of computing by navigating technical explorations and are passionate about building. 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: Manage the design and implementation planning of our ML acceleration hardware, working across technical, cross-functional and external stakeholders Lead planning and scheduling of chip hardware designs with our strategic partners and vendors Coordinate and marshal internal resources and communication for efficient interaction with partners and vendors. You might thrive in this role if you: Have experience as a technical program manager for data center hardware products (server, GPU, TPU, networking, storage and so on) Know the whole end-to-end system program management from concept, design, production, deployment into the data center Have some experience with System SW programs through NPI Want to help design some of the world’s largest supercomputing systems, working at the edge of complex hardware challenges Enjoy working with and enabling world-class AI Researchers and Engineers Are passionate about the technical program function, and enjoy independently owning and delivering on your tea

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 talented Physical Design Engineer to implement high-performance blocks for our industry-leading CPU and AI/ML architectures. You'll own the complete implementation flow from synthesis to tapeout, working alongside world-class engineers to push the boundaries of performance, power, and area. If you're passionate about crafting silicon that powers the future of AI computing and thrive on solving complex design challenges, we want you on our team. This role is hybrid, based out of Austin, TX or Santa Clara, CA or Fort Collins, CO. 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 hands-on engineer with deep expertise in SOC/ASIC physical design and a track record of successful tapeouts. Passionate about optimizing PPA through innovative implementation techniques and close RTL collaboration. Strong problem solver who excels at debugging complex issues across design hierarchies. Collaborative team player who thrives in fast-paced, technically challenging environments. What We Need BS/MS/PhD in EE/ECE/CE/CS with proven experience in synthesis, PnR, and timing closure on taped-out designs. Expertise with industry-stan

Principal Embedded SW/FW Engineer (Bringup) - Austin, Tx, USA 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 post-silicon validation. Working within the Post-Silicon 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. The Team The Post-Silicon Bringup team sits within the Architecture and Validation team, we are responsible for bringup and validation of new silicon when it returns from manufacture, enabling and supporting the production SW and FW teams to bring up their software and supporting the Silicon Characterisation team. Responsibilities and Duties Plan, design, develop and debug silicon validation tests in bare metal C/C++ on FPGA/Emulator prior to first silicon Deploy silicon validation tests on first silicon and debugging them Develop automated test framework and regression test suites in Python to optimize validation efficiency Collaborate closely with engineers from many other disciplines on a variety of topics Work with Validation and Production Test engineering peers to implement best practices and continuous improvements to test methodologies Analyse test results, identify and debug failures/defects Contribute to shared test and validation infrastructure Provide feedback to architects Candidate Profile Essential: Understanding of ML

Power and Performance Validation Engineer About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. 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. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Reporting to senior leadership within Architecture and Validation, the Power and Performance Validation Lead will drive validation strategy and execution for advanced AI compute silicon and systems. The role is responsible for leading power, thermal and performance validation activities across pre-silicon and post-silicon environments to ensure products meet efficiency, reliability and scalability expectations. This role requires strong technical expertise and collaboration across multiple engineering disciplines to deliver robust validation methodologies, scalable automation frameworks and actionable performance insights. The Team The Power and Performance Validation team sits within the Architecture and Validation organisation and is responsible for validating the performance, efficiency and thermal behaviour of Graphcore silicon and systems. The team supports the full product lifecycle, from early architectural modelling through to first silicon bring-up, characterization and production readiness. Engineers work closely with cross-functional teams globally to debug compl

Staff -Power and Performance Validation Engineer About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. 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. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Reporting to senior leadership within Architecture and Validation, the Power and Performance Validation Lead will drive validation strategy and execution for advanced AI compute silicon and systems. The role is responsible for leading power, thermal and performance validation activities across pre-silicon and post-silicon environments to ensure products meet efficiency, reliability and scalability expectations. This role requires strong technical expertise and collaboration across multiple engineering disciplines to deliver robust validation methodologies, scalable automation frameworks and actionable performance insights. The Team The Power and Performance Validation team sits within the Architecture and Validation organisation and is responsible for validating the performance, efficiency and thermal behaviour of Graphcore silicon and systems. The team supports the full product lifecycle, from early architectural modelling through to first silicon bring-up, characterization and production readiness. Engineers work closely with cross-functional teams globally to debu

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 senior High Speed Interconnect / Signal Integrity Engineer to design and validate high-bandwidth links for large-scale AI systems. You will define, model, and qualify interconnect solutions across copper and optical technologies for next-generation AI inference and training clusters. This role is on-site in Santa Clara, CA, Austin, TX, or Toronto, Canada. We welcome candidates at various experience levels. 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 An experienced electrical engineer with a Bachelor’s or Master’s in Electrical Engineering. 5+ years working on high-speed communications (100G–1.6T), including signal integrity, channels, and links. Comfortable building and owning link and channel budgets and making clear tradeoffs between reach, loss, BER, and margin. Hands-on with SI tools and lab equipment such as Keysight ADS, VNAs, TDRs, BERTs, and protocol analyzers. Familiar with cable specification and testing, as well as accelerated life testing, mating life, and failure analysis. Able to collaborate across hardware, systems, and manufacturing teams; manufacturing/DFM/DTM experience is a plus. What We Need Define and specify high-speed interconnect architectures

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 Signal Integrity Engineer to join our growing team. The ideal candidate will have a wealth of exposure designing high speed interconnects, breakout design, material trade-offs and verification. A background in electrical engineering, electronics or relevant fields is required. Must love all things high speed! This role is hybrid, based out of Santa Clara, CA or Austin, TX or Toronto, ON. 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 have a Bachelor’s degree in Electrical Engineering (or equivalent) and 5+ years working in high-speed digital design with a focus in high-speed PCB or package design at 10Gbps and above (e.g. 100GbE, GDDR6, PCIe Gen5+). You’re comfortable working with high-speed performance metrics such as ICR, ERL, COM, NEXT, and FEXT as well as knowledge of high-speed connector technologies, including NPO, CPO, and emerging standards. You are proficient with PCB ECAD tools (ideally Cadence Allegro). You communicate clearly (written and verbal), think critically, and love solving complex signal integrity problems. You’re enthusiastic about all things high speed and enjoy collaborating acro

NVIDIA’s Silicon Co-Design Group sits at the crossroads of architecture, silicon, systems, and manufacturing, where first-principles thinking and engineering judgment at the highest level translate directly into product outcomes at scale. We are looking for a Principal Performance and Manufacturing Architect who has built the models, defined the specs, and seen them validated through silicon. You have owned the connection between design intent and manufacturing reality, not as a reviewer or a contributor, but as the person who set the methodology and proved it worked. You turn ambiguous physical phenomena into quantified, defensible margin terms. You do not wait for data to confirm your hypothesis; you design the experiment that gets it. You improve how the organization ships products after every program. The exceptional hire also uses AI deliberately — with proven workflow impact and the judgment to know where it compresses real work and where it introduces risk. What you'll be doing: Own the physics, from mechanism to margin. Build first-principles models connecting AVF, defect mechanisms, and DVFS transients to field FIT, system-level yield, and DPPM vs. coverage — calibrated per node and population shift — so every margin term in the V/F curve and P-state table is named, sourced, and defensible. Set the screen that resolves escapes. Specify ATE and SLT voltage, frequency, and timing conditions that capture worst-case transient VF windows — making it unambiguous whether a marginal defect or timing violation is detected or escapes at every manufacturing stage. Make the POR the authoritative source. Author the methodology document for each program and drive alignment across build, product definition, reliability, and test engineering — so every team is making decisions from the same model. Prove the model before produc

NVIDIA’s Silicon Co-Design Group is the team that gets every GPU, SoC, and CPU silicon program from first power-on to high-volume production. We are hiring a Senior Manager to lead our Test, Manufacturability, Reliability & Quality (TMRQ) organization. This is not a coordination role . Your work decides if a product can be built at scale and trusted in the field. These include production test development (SLT, BLT), control run flow, system reliability stress (HTOL), platform- and board-level manufacturing issue closure, and field diagnostic test development. You lead a team of individual contributors and a first-line manager at the layer where silicon, platform, and software collide with manufacturing reality. Decisions you make show up in yield curves, production ramp , and customer escapes. You are the leader the program turns to when a build is stuck, a control run is fallout-heavy, or a field return points back at silicon . The exceptional hire also uses AI deliberately — with demonstrated workflow impact and the judgment to know where it compresses real work and where it introduces risk. What you will be doing: Keep programs moving. Own the technical execution and velocity of SLT, BLT, Board/Chip/Rack CR, and system reliability stress (HTOL) across every GPU, SoC, and CPU silicon program. Close the hardest multi-functional failures. Resolve Vmin and binning escapes, performance shortfalls, and power anomalies by driving root-cause across design, methodology, DFT, ATE, package, software/firmware, and manufacturing — and own the WARs and productized fixes through to confirmation. Give leadership the clarity to act. Convert raw integration signals — CR fallout, BLT/SLT yield, SHTOL/CHTOL data, RMA trends, customer escalations — into decision-ready options that enable executive leadership to act with confidence on POR, QS/PS gates, a

NVIDIA builds the silicon behind AI, accelerated computing, and graphics. Every watt of performance and every degree of thermal headroom traces back to decisions made in power, performance, and thermal architecture. We are the Silicon Co-Design Group (SCG). We identify, own, and drive system-level co-design ideas. We start with initial concepts and advance to product differentiation across NVIDIA's roadmap. We are hiring a Principal System Power Management and Performance Architect who operates at the ambiguous boundary where workload behavior, silicon capabilities, firmware policies, and platform constraints collide, and who turns that ambiguity into architecture that survives across multiple silicon generations. SCG scope spans architecture, design, software, operations, platforms, and productization. This role shapes system, platform, and data center features and behavior, and partners with teams across NVIDIA. What You'll Be Doing: The work here is rarely well-defined when it arrives. You will be given problems that appear to be performance gaps or power anomalies and encouraged to build a framework for solving them, not just tackle a single instance. Define the multi-generation roadmap for system-level power and performance features, grounded in prototyping, use-case analysis, and cost/benefit trade-offs across segments. You will decide what problems are worth solving and why. Own the architecture and integration strategy for HSIO power management, DVFS, P-states, and low-power features. Your decisions improve product performance, power, and reliability across product lines — not just the current program. Lead system-level boot and IST architecture defining how power and clock domains initialize, sequence, and recover across complex multi-IP systems where the interaction space is large and the failure modes matter. Drive power management strategy at data

About the Team The Stargate team is responsible for building the physical infrastructure that powers large-scale AI systems. We design and deliver next-generation data centers optimized for dense compute clusters, advanced networking, and rapidly evolving hardware platforms. This work sits at the intersection of hardware engineering, systems architecture, and infrastructure execution—translating cutting-edge compute roadmaps into scalable, production-ready environments. Our teams partner across silicon vendors, server and storage OEMs, networking teams, and data center engineering organizations to bring new capacity online quickly, reliably, and at global scale. About the Role We are seeking a CPU & Storage Technical Lead to define and drive the server compute and storage architecture strategy for Stargate infrastructure. In this role, you will own technical direction across CPU platforms, memory configurations, local and disaggregated storage systems, and their integration into large-scale AI clusters. You will evaluate vendor roadmaps, lead platform tradeoff decisions, and ensure compute and storage systems are optimized for training, inference, and supporting services. You will work cross-functionally with hardware engineering, performance modeling, networking, supply chain, and deployment teams, as well as external partners such as AMD, Intel, OEMs, ODMs, and storage vendors. This is a highly strategic role for someone who can operate deeply at the component level while also driving long-range infrastructure decisions. Key Responsibilities Own CPU and storage technical strategy for Stargate compute infrastructure across current and future generations. Evaluate CPU platforms across performance, efficiency, memory bandwidth, PCIe topology, cost, and roadmap alignment. Define storage architectures for AI environments, including boot media, local NVMe, shared storage, caching tiers, metadata services, and high-performance data pipelines. Drive server platform de

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 Rack Power Engineer with deep expertise in high-power conversion and distribution to design, qualify, and support power systems for AI supercomputers. You will own rack power solutions—including power shelves, AC/DC rectifiers, power supply units (PSUs), power management controllers (PMCs), and high-current distribution—from requirements and supplier development through deployment. You will also monitor fleet rack power health, lead debugging and root-cause investigations, and drive improvements into hardware, firmware, and qualification coverage. 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 rack power architecture and requirements for high-power AI supercomputing systems, including power budgets, AC input interfaces, DC distribution, redundancy, efficiency, serviceability, and integration with data center infrastructure. Drive the design and supplier development of power shelves, rectifiers, PSUs, PMCs, busbars, connectors, and protection circuits. Review electrical designs and control behavior, and evaluate performance, cost, reliability, and availability trade-offs. Define and execute component, shelf, and rack qualification plans covering load transients, current sharing, hot-swap, startup and shutdown, redundancy failover, fault protection and recovery, thermal limits, and AC disturbances and ride-through

NVIDIA's Silicon Co-design Group (SCG) sits at a rare intersection: we own the full product development lifecycle, from early architecture definition through silicon bringup to product release. Our ArchDev team is the hub for silicon and system-level feature development, driving tradeoff analysis, system integration, and POR alignment across the entire organization. If you want to see your work go from whiteboard to world-class silicon, this is where that happens. What You'll Be Doing: Architect and integrate system-level performance and power management features, controllers, and policies to optimize product efficiency across datacenter and client products . Build feature roadmaps to address low-power, low-noise, and performance-per-watt product needs through prototyping, use-case analysis, and cost/benefit trade-offs. Partner with architecture, ASIC, board/platform, software/firmware, and marketing teams to drive design decisions and debug complex issues. Track industry trends and market needs and translate them into forward-looking roadmaps that keep NVIDIA's products ahead of the curve. Lead debug efforts, develop workarounds, and support bringup , validation, manufacturing, and customer escalations. What We Need to See: <

About the job Lead the team that proves our AI silicon performs reliably before it reaches customers. You will build and lead Graphcore's characterisation capability for next generation silicon and system platforms. Your work will help ensure our products perform consistently across real world conditions. You will define bring up and characterisation strategies, lead technical execution, and shape the lab infrastructure needed for success. You'll work across silicon, hardware, manufacturing, architecture and product teams to solve complex engineering challenges. This is a hands on leadership role with the opportunity to influence both product design and how Graphcore validates future AI systems. The team and culture This is a newly formed team within Manufacturing Operations. You'll have the opportunity to establish how the team works while building strong partnerships across engineering and operations. Day to day, you'll work closely with architecture, silicon, hardware, production test and product teams. Decisions are driven by data, technical evidence and close collaboration across disciplines. We value ownership and clear communication. You'll be trusted to lead technical direction, remove blockers and help teams make progress with confidence. What we're looking for Essential Proven track record of delivering complex technical projects as an individual contributor, manager, or project manager, with the ability to work independently and drive execution. Strong expertise in silicon digital device design, bring-up, characterisation, and silicon process technologies, with an understanding of their impact on transistor- and system-level performance. In-depth knowledge of high-performance processors, system-on-chip (SoC) architectures, and high-speed digital interfaces such as PCIe, Ethernet, and DDR. Experience with measurement automation, data analysis, and scripting/coding to develop automated test and analysis workflows, with familiarity of ATE systems and t

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role We are looking for an experienced Mechanical Engineer with 7+ years of experience in design of IT hardware from chip/package to system levels. You’ll work alongside experts in thermal, mechanical, electrical, software, and systems engineering to support the design, analysis, and validation of mechanical and thermal systems that ensure the reliability, efficiency, and longevity of mission-critical hardware. This position requires strong analytical skills, hands-on testing experience, and the ability to work in a fast-paced, cross-disciplinary environment. 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: Lead mechanical design for AI supercomputer product in the data center application Collaborate with the cross functional team to design and optimize thermal solutions for data center hardware, including chips, power modules, and system-level cooling architectures Collaborate with cross-functional teams to integrate thermal management strategies into hardware design, from concept to mass production Design and validate mechanical systems, including chassis, enclosures, cooling systems, and high-power connections, ensuring alignment with performance and reliability standards. Perform 3D modeling, FEA, tolerance analysis, and prototyping, ensuring manufacturability and a