Silicon Power And Characterization Lead in United States

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. NVIDIA’s Silicon Co-Design Group is hiring a Chip Lead to serve as the technical lead for one of our most consequential silicon programs! This is not project management, and it is not a senior IC role. You are the person the program partners with on its hardest technical questions — when the right answer is not obvious, and when leadership needs a single technical perspective to align on direction. You are accountable for the technical integrity of the chip end-to-end. You guide co-design feature integration, help resolve the toughest multi-functional bugs, and serve as the project-specific custodian of the qualification playbook. The program runs cleaner because you are on it! What you’ll be doing: You will partner across design, validation, software, and manufacturing to keep the program’s technical narrative clear and on track. Day to day, you will: Serve as the single technical point of contact for multi-functional decisions, issues, and trade-offs. Co-lead program-level feature integration from chip to system, surfacing inter-function dependencies and guiding them to resolution. Help resolve the program’s hardest multi-functional bugs by translating ambiguous, multi-team symptoms into root-cause closure on areas such as HBM, power and thermal, high-speed I/O, and packaging. Steward the qualification playbook. When the playbook does not fit a situation, guide the mitigations and capture the lessons as reusable methodology for other SSG programs. Shape the program’s technical narrative by surfacing key risks, trade

NVIDIA is seeking a world-class computer architect to contribute to the development of future high-performance computing systems, with a focus on enhancing the power-constrained performance of the hardware. Ideal candidates will have a strong track record of understanding and analyzing memory systems architecture to improve performance per watt (perf/W) and performance per millimeter (perf/mm). A broad perspective across the field of computer architecture and depth in the area of power, performance, and area (PPA) analysis is highly desirable. NVIDIA has pioneered programmable GPUs and the CUDA language and is a world leader in high-performance computing technology, with aggressive plans for future processors. This position offers the opportunity to have a real impact in a fast-moving, technology-focused company. What you will be doing: Develop innovative high-performance processor and system architectures, focusing on the memory system and energy efficiency. Develop architecture and micro-architecture features to improve the state-of-the-art in GPU memory systems, optimizing along the axes of perf/W, perf/mm, and perf/$. Develop and enhance architecture prototype models for power and noise analysis. Participate in performance and power simulation of features to analyze, define, and improve energy per byte. Analyze benchmarks, application workloads, and performance/power simulation and emulation results to identify areas for architecture optimizations. Debug power, performance, and functional issues with high-level models, RTL simulation and emulation, silicon, and systems. Collaborate with outside partners on system infrastructure. What we want to see: 10+ yrs of experience in CPU/GPU architecture, memory systems design with a focus on energy efficiency in the system. Bachelor

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

Define the physical limits of what a chip can do, then break them! NVIDIA's Silicon Co-Design Group sits at the crossroads of architecture, silicon, systems, and manufacturing, where first principles thinking translates directly into product outcomes at scale. As GPU power density and thermal limits approach physical boundaries, the gap between system architecture needs and manufacturable, testable capabilities widens with every generation, and this role exists to close it. You wouldn't be maintaining existing solutions, you'd be identifying where physical constraints will erode NVIDIA's competitive edge before anyone else sees it coming, then building the cross-domain responses that ensure the next generation leapfrogs those limits entirely. The problems here don't have known answers yet: Every generation of NVIDIA silicon pushes closer to the limits of physics. The Co-Design Architect role isn't about optimizing within known bounds; it's about redrawing those bounds entirely. If you want your work to shape what's physically possible in the world's most demanding computing products, this is where that work happens. What you'll be doing: Power, Thermal & Packaging Limits Analysis: Gather and analyze the hard constraints of packaging, power delivery, and thermal dissipation against roadmap demands, predicting when those constraints will reduce competitiveness and acting before they do. Cross-Domain Solution Development: Develop solutions that span silicon features, packaging innovation, firmware and hardware co-design, and DFX updates, ensuring future products are not only performant but testable to the highest quality and reliability standards. Packaging Technology Evaluation: Assess emerging packaging technologies for their voltage/frequency, noise, reliability, and testability implications, determining which are worth adopting an

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 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

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 a best-in-class 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 a diverse group of 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 We are seeking a senior validation lead engineer to lead at-scale rack validation efforts for next-generation AI hyperscale systems. This role focuses on post-silicon system validation across the full lifecycle, ensuring functional, electrical, and thermal performance meets product objectives. You will own end-to-end blade and rack validation including planning, development, execution, and debug while collaborating across firmware, systems, and hardware teams. The Team The 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. Responsibilities and Duties Lead post-silicon validation of AI compute blades and racks including test planning, development, and automation. Drive provisioning and integration of system components (SoC FW, BMC, RMC, OS) for rack-level readiness. Own execution against program achievements and report validation progress and risks. Triage test failures, collect debug data, and collaborate on root cause analysis. Track

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. Role Overview We are seeking an experienced ASIC Package Signal Integrity / Power Integrity Engineer to drive electrical architecture, modeling, optimization, and validation for the most advanced AI/HPC silicon and package design. This role focuses on high-speed SerDes and memory channel architecture, advanced 2.5D/3D package SI/PI, substrate to package co-design, power-delivery-network optimization, electromagnetic modeling, and simulation-to-measurement correlation. The ideal candidate has strong hands-on experience with high-speed channel and PDN analysis across ASIC packages, interposers, substrates, and power-delivery structures, and can translate simulation results into practical design requirements for interposers and package substrate design optimization. The engineer will work closely with ASIC, package, system, mechanical, thermal, power, and silicon validation teams from early architecture and feasibility studies through production bring-up. In this role you will Own SI/PI architecture and analysis for advanced AI ASIC packages from early feasibility studies through production. Develop and optimize high-speed electrical channels for 200G/400G SerDes, PCIe, HBM, DDR, and chiplet/die-to-die interfaces. Perform package, interposer and substrate modeling using 2D/3D electromagnetic solvers. Define and optimize package stack-ups, transmission-line structures, via transitions, breakout structures, return paths, ground shielding, bump maps, and ball maps based on SI/PI re

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 We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

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 We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

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 We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

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 We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

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 We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

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 We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

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 are seeking a highly skilled Physical Design Engineer with deep expertise in physical design and methodology. This individual contributor role sits within our physical design team and is central to delivering power, performance, and area (PPA) optimized datapath and interconnect solutions for next-generation AI accelerators. You’ll work closely with RTL designers to define and execute on physical design strategies. You will develop tools, flows and methodologies to increase team productivity. Your work will directly impact silicon’s performance and cost efficiency, as well as the team’s execution velocity and quality. In this role, you will: Develop, build and own tools, flows and methodologies for physical implementation Own physical implementation of floorplan blocks from floorplanning to final signoff Collaborate with RTL designers to drive optimal block implementation solutions Analyze and optimize design for timing, power, and area trade-offs, working in collaboration with EDA vendors and ASIC partners Qualifications: BS w/ 4+ or MS with 2+ years or PhD with 0-1 year(s) of relevant industry experience in physical design and methodology development Demonstrated success in taping out complex silicon designs Hands-on experience with block physical implementation and PPA convergence Strong coding experience with python, bazel, TCL Strong experience building physical design tools, flows and methodologies Strong understanding of microarchitecture, RTL design,