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
Jobs in United States
Silicon Power And Characterization Lead in United States
192 active opportunities · Updated October 2026
Showing
15 jobs
Explore current silicon power and characterization lead jobs across United States. Filter by work mode, employment type, experience, department, date posted and distance.
Job Details: Job Description: Intel Corporation is the world's largest semiconductor company and a global leader in computing innovation. Our Quantum Computing Group represents Intel's bold venture into the next frontier of computing technology, leveraging our decades of semiconductor manufacturing expertise to develop silicon-based quantum processors. We're pioneering spin qubit technology in silicon quantum dots, combining cutting-edge quantum physics with Intel's unmatched manufacturing capabilities to create the world's first commercially viable quantum computers. Our collaborative approach spans Intel's research divisions and partnerships with leading academic institutions worldwide. We are seeking an exceptional Quantum Packaging Signal/Power Integrity (SI/PI) Engineer to join our pioneering quantum computing team in Oregon. In this role you will be responsible for modeling and simulation of various packaging solutions from silicon redistribution layers to IC substrates within a multidisciplinary team. You'll play a crucial role in advancing Intel's silicon quantum dot technology while contributing to the development of scalable quantum systems that will revolutionize computing. Key Responsibilities - Modeling and simulation of packaging hardware including redistribution layers (e.g., interposers, RDLs), IC substrates, and silicon testchip routing - Work closely with stakeholders to meet design requirements - requirements come from both theory and hardware teams. In some pathfinding projects, you will be asked to participate in creating requirements and novel packaging hardware. - System-level modelling and simulation; end-to-end simulations to ensure designs meet system-level requirements - Deliver and disseminate design milestones to stakeholders - Communicate designs in pr
NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can address, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today. Design-for-X Engineering at NVIDIA works on groundbreaking innovations involving crafting creative solutions in AI for Chip Design and AI for Predictions in various use cases in manufacturing testing on some of the industry's most complex semiconductor chips. What you'll be doing: As a senior member in our team, you will work on innovating in the DFT Power, Thermal & Voltage Noise Methodology areas. This will include working on groundbreaking low power & thermal solutions for our manufacturing tests to be enabled at conditions that push the boundaries for our datacenter GPUs. You will work with multi-functional teams including Product Development & Power Architecture, implementing brand-new methodologies on hard-to-solve problems for improving our outgoing quality of chips. You will work on post-silicon data analysis for power to architect the next-gen solutions. In addition, you will help develop and deploy DFT methodologies for our next generation products using Applied ML & Gen AI solutions. You will also help mentor junior engineers on test designs and trade-offs including cost and quality. What we need to see: BSEE (or equ
$100K – $500K/yr
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
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 seeking a System Software Engineer to join our First-Party Hardware team. In this role, you will design, build, integrate, and validate low-level system software for the manageability and health of OpenAI's first-party AI hardware systems. You will work across BMC, Linux, firmware interfaces, automation infra, boot and recovery, hardware diagnostics, telemetry, host and platform drivers, network software interfaces, and manufacturing and fleet readiness. A major part of this role is owning the acceptance path for partner-delivered system software: defining requirements, reviewing code and artifacts, reproducing builds, building tests, pushing fixes, and producing the evidence needed for launch decisions. This role is hands-on and high-ownership. You will write and review low-level software, debug issues across hardware and software boundaries, build infra and automation to test and manage devices in lab, guide partner deliverables, build validation evidence, and help carry platforms from bring-up through production deployment. Location: San Francisco, CA (Hybrid: 3 days/week onsite) Relocation assistance available. In this role, you will: Design, develop, and maintain low-level firmware and system software for first-party AI hardware manageability, including BMC software, Redfish services, gNMI telemetry, firmware update and recovery flows, BIOS/UEFI interactions, platform drivers, and hardware diagnostics. Own integration and acceptance of partner and ve
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 seeking a Software Engineer to join our First-Party Hardware team. In this role, you will design, build, integrate, and validate the software used to manufacture, qualify, and deliver our hardware from the factory. You will work across the stack to create the infrastructure that runs internally and externally to coordinate all aspects of the production process. You will create the critical tools and procedures to execute, capture, process, and present the data resulting from the end to end assembly and validation of our hardware across multiple vendors and sites. This role is hands-on and high-ownership. You will work closely across teams both internal and external to define the standards that will be used across our products to ensure the velocity and quality of our 1P hardware. You will own the implementation, deployment, and output of these systems as well their continued maintenance and SLAs. Location: San Francisco, CA (Hybrid: 3 days/week onsite). Relocation assistance available. In this role, you will: Design, develop, and maintain the software infrastructure for manufacturing process execution and data export. Own integration across internal customers and vendor systems and processes. Build and maintain the CI, release, and delivery pipeline of tooling to external partners. Build and maintain internal systems to ingest, process, deliver, and visualize critical data for internal teams and systems. Build system health monitoring, telemetry, remote d
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 summary We are seeking a Networking Operating System Firmware Engineer to help bootstrap and scale the switching layer of our AI supercomputers. In this role, you will build and maintain custom NOS images from scratch, using open source components from SONiC, SAI, FRR, and related networking stacks while working across the Linux kernel, switch ASIC SAI/SDKs, platform drivers, control-plane services, and orchestration layers. This is a software engineering role that requires a deep understanding of networking, NOS internals, switch hardware, and production systems. You will design, implement, test, and debug production NOS software across platform drivers, routing and control-plane state, ASIC programming, observability, and fleet integration. The engineer in this role should be able to work through ambiguous, open-ended technical problems and drive feature development across software, hardware, and vendor boundaries. 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 Design, develop, and maintain custom NOS images for large-scale AI fabrics, using open source components from SONiC, FRR, and related networking stacks. Integrate, build and configure Linux kernel components, device drivers, switch ASIC SDKs, and SAI layers. Bring up new switch platforms, including thermal and fan control, power monitoring, transceiver management, watchdogs, OSFP CMIS, L
About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for a product manufacturing & quality engineer, who will be responsible for driving technical initiatives related to the manufacturing, quality and reliability of our AI supercomputer hardware systems to ensure product success from concept to launch and through mass production. You’ll have the opportunity to coordinate with functional SMEs and work with a wide range of stakeholders, from design engineering and operations teams, TPMs, external industry vendors and partners to ensure that all products are developed and delivered on time and to the highest quality standards. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees In this role, you will: Own the integrated manufacturing and quality readiness for a product across L6, L10, and L11, with clear gates, milestones, deliverables, owners, and closure criteria. Lead readiness of process flows, tooling, fixtures, assembly operations, test interfaces, and production controls. Review and contribute to work instructions. Translate product requirements into qualification plans, process controls, test requirements and acceptance criteria with design engineering and Area SMEs Coordinate and drive execution of product and process qualification, reliability testing, and validation with the relevant SMEs. Maintain traceable evidence that assigned products and processes meet agreed performance, reliability,
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. In this role you will: As a Hardware Test Engineer, you will work on Machine Learning/AI hardware system projects to craft the solutions for current and future data center deployments. You will bring a strong understanding of hardware system testing, excellent project management skills, and the ability to collaborate across multiple teams to ensure efficient lab operations. You will be responsible for designing, implementing, and executing comprehensive test plans that ensure the reliability, performance, and scalability of our supercomputing hardware systems. You will develop detailed test plans and methodologies tailored to hardware components, including processors, memory modules, custom accelerators and interconnects. You will collaborate with hardware design, manufacturing, firmware teams and vendors to identify, analyze, and resolve issues affecting hardware, power, thermal and high-speed interconnects. You will perform in-depth debugging on the hardware system Excellent analytical skills to diagnose hardware issues, troubleshoot problems, and propose solutions. Ability to interpret complex test data, identify trends, and draw meaningful conclusions. High-speed links, with a focus on SerDes (Serializer/Deserializer) technology to assess signal integrity, error rates, and overall link performance. You will collaborate with the lab manager to maintain the equipment and hardware systems, including oscilloscopes, thermal test chambers, liquid cooling systems, and other mea
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 build the model runtime within the inference engine that executes complex, frontier models at scale on OpenAI’s custom silicon. The runtime will sit between models running on the hardware and the upper layers of the cluster serving software stack, translating demanding inference workloads into efficient execution while optimizing for throughput, latency, utilization, and reliability. You will work across model architecture, distributed systems, compilers, kernels, and silicon to design a production-grade runtime comparable in ambition to systems such as vLLM and SGLang, but customized and optimized for OpenAI’s AI accelerator. Your work will shape how new model capabilities map onto the platform and how quickly custom silicon can deliver meaningful performance in production. In this role, you will: Design and implement the LLM inference runtime for frontier models running on custom silicon. Build scheduling, continuous batching, memory management, KV-cache management, and execution orchestration for high-performance inference. Develop distributed execution strategies across chips, hosts, and racks, including model partitioning, communication, and synchronization. Optimize end-to-end latency, throughput, memory efficiency, and hardware utilization across diverse model architectures and serving workloads. Partner with kernel, compiler, architecture, and silicon teams to co-design interfaces and remove performance bottlenecks across the stack. Enable new
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 build the low-level device runtime that turns compiled programs into efficient, functional and performant execution on OpenAI’s custom AI accelerator. This software will schedule kernel launches, manage device memory and address spaces, coordinate synchronization, and expose reliable abstractions to higher-level runtimes and frameworks. You will work at the boundary of software and hardware, partnering with compiler, kernel, architecture, verification, and silicon teams to define interfaces and validate behavior. You will also use and improve event-based, cycle-accurate simulation to develop runtime capabilities before silicon is available, diagnose performance and correctness issues, and guide hardware-software co-design. In this role, you will: Design and implement the low-level device runtime for OpenAI custom silicon. Build kernel-launch scheduling, command submission, queueing, dependency tracking, and completion handling. Manage device memory spaces, allocation, virtual-to-physical mappings, data movement, and lifetime across concurrent workloads. Implement synchronization primitives, events, barriers, streams, and ordering guarantees that are correct and efficient. Define clean interfaces between the runtime, drivers, firmware, compiler-generated code, kernels, and higher-level execution systems. Use event-based, cycle-accurate simulators to develop, validate, debug, and performance-tune runtime behavior before and after silicon availability. Di
About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for a Product Manufacturing Engineer to drive manufacturing strategy and execution for next-generation AI hardware within the Silicon & Systems team, with a particular focus on PCBA manufacturing, assembly, process development, and production readiness. You will work closely with design engineering, systems engineering, operations, TPMs, contract manufacturers, suppliers, and other external partners to ensure new hardware products successfully transition from concept and prototype builds through NPI and high-volume production. You’ll own critical manufacturing initiatives, identify and resolve production risks, and help establish the processes and controls required to deliver complex hardware at scale. 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: Drive manufacturing and quality initiatives to ensure product success from concept and early development through NPI, production launch, and scale. Lead manufacturing process development for next-generation AI hardware systems, partnering closely with design engineering, systems engineering, operations, TPMs, suppliers, and manufacturing partners. Own PCBA manufacturing development and production readiness, including assembly processes, process validation, manufacturing test, rework, yield improvement, and successful transition into volume production. Establish NPI manufact
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 an AI Accelerator Systems Software Technical Program manager at OpenAI, you will help bring our chips/system 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 end-to-end software development from design to implementation for our AI acceleration systems, working across technical, cross-functional and external stakeholders Lead planning and scheduling of AI system software designs with our strategic partners and vendors Coordinate and lead internal resources and communication for efficient interaction with partners and vendors. You might thrive in this role if you: Have experience as a software technical program manager for data center system products (server, GPU, TPU, networking, storage and so on) taking products from concept to volume in a data center environment ensuring the systems scale with high quality Know end-to-end software development program management techniques from concept, design, production, deployment into the data center 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-clas
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 looking for a highly experienced RTL engineer to own critical on- and off-chip interconnect components for our custom AI accelerator platform. You will drive the microarchitecture and RTL implementation of scalable on-chip communication fabrics connecting high-bandwidth compute, memory, and I/O subsystems as well as purpose-built off-chip interfaces and protocols needed to enable custom computing at scale. This is a senior, hands-on engineering role with broad technical ownership. You will drive design from requirements through the full silicon lifecycle, from architecture definition and performance analysis through RTL implementation, verification closure, physical design convergence, bring-up, and production readiness. You will plan and oversee the work of junior engineers and help drive and develop productive engineering relationships with external partners and help manage partner execution. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own the microarchitecture, RTL design, and delivery of major SoC interconnect components, including network-on-chip fabrics, switches, routers, bridges, protocol adapters, arbiters, and traffic-management logic as well as off-chip protocol bridges and interfaces. Drive third party engagements to develop novel networking and interface protocols and silicon IP while ensuring high quality and 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. Role Overview We are seeking a Package Reliability Engineer to lead reliability engineering for advanced packages used in high-performance AI and computing systems. The primary focus of this role is to assess package level mechanical and thermal reliability risks and apply thermal and mechanical modeling to optimize package design, material selection, and assembly processes. The engineer will also develop reliability test plans with external partners, identify failure mechanisms, perform root-cause analysis, and recommend practical corrective actions. In this role, you will assess package reliability risks from early architecture development through product qualification and high-volume manufacturing. You will work closely with package design, silicon design, system engineering, manufacturing, and ASIC partners to predict package behavior, develop qualification strategies, resolve reliability issues, and improve overall package robustness and lifetime. In this role you will: Lead reliability test plan and assessments for advanced HPC packages, including risk identification, potential failure-mechanism analysis, root-cause investigation, mitigation planning, and corrective-action development. Drive reliability-focused package design optimization based on thermo-mechanical modeling to improve package reliability, power integrity, thermal performance, mechanical robustness, and platform scalability. Develop, validate, and apply package reliability models and lifetime-prediction
Other cities to consider
More places hiring for this role
Get new silicon power and characterization lead jobs in United States by email
Daily job updates · Unsubscribe anytime