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Hardware Operations Engineer in San Francisco

184 active opportunities · Updated October 2026

Explore current hardware operations engineer jobs in San Francisco. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -86.4%

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role OpenAI is seeking to build an investigative capability for Secure Manufacturing & Stealth programs. The risk surface for unreleased products, prototypes, confidential hardware, infrastructure, supply chain, manufacturing, and launch-readiness efforts spans employees, vendors, suppliers, logistics partners, physical movement of assets, procurement records, manufacturing workflows, access systems, device telemetry, and adversarial collection. This role is intended to build and run investigations across that specialized environment. In this role, you will: Lead complex SMS investigations to proactively identify and mitigate risks to unreleased products, prototypes, confidential hardware, secure manufacturing programs, and launch-readiness efforts. Investigate unauthorized disclosure, suspected leaks, insider risk, supplier compromise, vendor misconduct, theft, diversion, tampering, counterfeiting, surveillance, adversarial collection, and suspicious activity involving sensitive programs. Connect digital evidence, physical access activity, supply chain records, manufacturing data, vendor behavior, employee activity, collaboration metadata, procurement records, shipping data, and OSINT into clear findings and risk-reduction actions. Conduct proactive threat hunting to surface early indicators of compromise, collection, leakage, or insider activity affecting sensitive programs. Develop investigative playbooks, evidence-handling standards,

AWSGitRestAI
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📍 San Francisco, California, United States
✓ Quality checkedCompany trend -96.2%

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The role We are seeking a Director of Digital Employee Experience to lead the strategy and execution of a modern, intuitive, and measurable digital workplace experience for our employees. This leader will own the strategy and technology experience for how employees access the tools, information, services, and support they need to do their best work. The ideal candidate is a systems thinker and cross-functional operator who can connect business needs, employee insights, technology capabilities, service design, and change management. This role will partner closely with IT, People/HR, Security, Workplace, Communications, and business leaders to simplify employee journeys, increase technology adoption, and reduce friction across the digital workplace. What you’ll do Develop and own the employee digital experience vision, strategy, roadmap, and operating model. Drive SoFi’s “Make Work Easier” strategy by identifying and reducing friction across the digital employee experience, making it simpler for employees to find information, access support, and get work done. Map and improve priority employee journeys, including onboarding, internal mobility, hardware/software access, IT and HR support, knowledge discovery, collaboration, and hybrid work experiences. Partner with service owners across IT, HR, Facilities, Sec

AIFinanceProcurementHR
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📍 San Francisco, California, United States· Full-time
✓ High-confidence listingCompany trend -86.4%
Quick readStrong listing-quality and freshness signals

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team builds next-generation AI-native silicon and systems while working closely with software, research, and manufacturing partners to co-design hardware tightly integrated with AI models. In addition to delivering systems for OpenAI’s supercomputing infrastructure, the team develops the tools, methodologies, and strategic partnerships needed to accelerate hardware innovation. About the Role We’re seeking an experienced Hardware Strategic Sourcing Manager to own sourcing strategy and supplier partnerships for fiber and optical interconnect components across OpenAI’s next-generation AI infrastructure. Reporting to the Head of Partnerships & Strategic Sourcing, you will lead sourcing across fiber cable assemblies, internal optical harnesses, fiber shuffles, optical backplane assemblies, connectorized and standalone passive optical assemblies, fiber-array units (FAUs), fiber-to-chip and coupling interfaces, detachable connectors, optical routing, and assigned optical packaging, assembly, and test services. You will work closely with electrical engineering, optical engineering, systems engineering, mechanical and packaging engineering, quality, rack integration, data-center deployment,manufacturing, supply chain, finance, legal, and program management teams to translate demanding bandwidth, signal integrity, reliability, and scale requirements into resilient supplier partnerships and scalable commercial strategies. Your work will directly support the performance, reliability, manufacturability, and scale of the high-speed optical connectivity required for OpenAI’s next-generation AI systems. In this role, you will: Develop and execute a comprehensive sourcing strategy for fiber and optical interconnect components supporting high-bandwidth AI systems and infrastructure. Own sourcing across optical fiber cable assembli

AWSRestAIGo
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -86.4%

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 develop and evolve the tooling ecosystem that hardware engineers rely on every day — from hardware compilers and IR transformations to simulation, debugging, and automation infrastructure. The work spans software engineering, compiler concepts, and practical hardware workflows, with direct impact on how quickly and effectively we design next-generation AI systems. You’ll collaborate closely with architects, RTL designers, and verification engineers to translate real engineering friction into durable, scalable tooling solutions. In this role you will: Build and improve the software tooling that makes hardware teams faster: compilation, IR transforms, RTL generation, simulation, debug, and automation. Extend and integrate hardware compiler stacks (frontends, IR passes, lowering, scheduling, codegen to Verilog/SystemVerilog) and connect them to real design workflows. Improve developer experience and reliability: reproducible builds, better error messages, faster iteration loops, and dependable CI and regression infrastructure. Work closely with designers and verification engineers to turn real pain points into durable tools. Dive into RTL when needed: read and reason about Verilog/SystemVerilog to debug issues, validate tool output, and improve debuggability. Be willing to go all the way down the stack when necessary, including gate-level views, synthesis results, and implementation artifacts. Help enable PPA optimization loops by building analysis and au

PythonAWSGitRest
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Relocation support. Relocation assistance is stated. This does not establish visa sponsorship.
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -86.4%

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 As an Engineer on our hardware optimization and co-design team, you will co-design future hardware from different vendors for programmability and performance. You will work with our kernel, compiler and machine learning engineers to understand their unique needs related to ML techniques, algorithms, numerical approximations, programming expressivity, and compiler optimizations. You will evangelize these constraints with various vendors to develop and influence future hardware architectures towards efficient training and inference on our models. If you are excited about efficiently distributing a large language model across devices, dealing with and optimizing system-wide/rack-wide networking bottlenecks and eventually tailoring the compute pipe and memory hierarchy of the hardware platform, simulating workloads at different abstractions and working closely with our partners, this is the perfect opportunity! 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. Key Responsibilities Co-design future hardware for programmability and performance with our hardware vendors Assist hardware vendors in developing optimal kernels and add support for it in our compiler Develop performance estimates for critical kernels for different hardware configurations and drive decisions on compute core and memory h

PythonAWSRestMachine Learning
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Relocation support. Relocation assistance is stated. This does not establish visa sponsorship.
📍 San Francisco, California, United States· Full-time
✓ High-confidence listingCompany trend -86.4%
Quick readStrong listing-quality and freshness signals

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

AWSRestAIRust
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Relocation support. Relocation assistance is stated. This does not establish visa sponsorship.
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -86.4%

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 software engineer on the Scaling team, you’ll help build and optimize the low-level stack that orchestrates computation and data movement across OpenAI’s supercomputing clusters. Your work will involve designing high-performance runtimes, building custom kernels, contributing to compiler infrastructure, and developing scalable simulation systems to validate and optimize distributed training workloads. You will work at the intersection of systems programming, ML infrastructure, and high-performance computing, helping to create both ergonomic developer APIs and highly efficient runtime systems. This means balancing ease of use and introspection with the need for stability and performance on our evolving hardware fleet. This role is based in San Francisco, CA, with a hybrid work model (3 days/week in-office). Relocation assistance is available. In this role, you will: Design and build APIs and runtime components to orchestrate computation and data movement across heterogeneous ML workloads. Contribute to compiler infrastructure, including the development of optimizations and compiler passes to support evolving hardware. Engineer and optimize compute and data kernels, ensuring correctness, high performance, and portability across simulation and production environments. Profile and optimize system bottlenecks, especially around I/O, memory hierarchy, and interconnects, at both local and distributed scales. Develop simulation infrastructure to validate runtime b

PythonAWSRestAI
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Relocation support. Relocation assistance is stated. This does not establish visa sponsorship.
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -86.4%

About the Team OpenAI's Legal team plays a crucial role in furthering OpenAI's mission by tackling innovative, fundamental legal issues in AI. If you're passionate about doing significant and unique work as a technology lawyer, this team is for you. The team comprises legal professionals from diverse fields, including technology, privacy, IP, corporate, cybersecurity, employment, tax, regulatory, and litigation. About the Role We’re growing our world-class Legal team and seek an experienced counsel to lead our global hardware IP portfolio initiatives, including patent, trademark and other intellectual property matters related to our business. This role is highly cross-functional across OpenAI, including work across our Legal, Communications, Global Affairs, Product, Research and Executive teams. 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 global hardware IP initiatives, including setting and executing on the strategic direction and management of our hardware IP portfolio. Create scalable processes internally and externally with outside counsel to build, maintain and protect our hardware IP portfolio. Developing and maintaining internal hardware IP policies and programs. Engaging externally on hardware IP policy issues. Advising on strategic hardware IP deals. Advising on hardware IP issues, ranging from patent, trademark, trade secret to open source. Developing and building internal AI expertise, processes and tools to facilitate legal team work. Experience advising on complex technology transactions and inbound technology licensing. You might thrive in this role if you: Have at least 10+ years of combined hardware IP experience at innovative technology companies and law firms. Have a JD and license or qualification to practice in CA. Have a strong sense of ownership, are inquisitive and enthusiastic about technology, enjoy being con

AWSRestAIRust
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -86.4%

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

AWSRestAIRust
O
Relocation support. Relocation assistance is stated. This does not establish visa sponsorship.
📍 San Francisco, California, United States· Full-time· Remote
✓ High-confidence listingCompany trend -86.4%
Quick readStrong listing-quality and freshness signals

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

PythonArtificial IntelligenceAI
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Relocation support. Relocation assistance is stated. This does not establish visa sponsorship.
📍 San Francisco, California, United States· Full-time· Remote
✓ High-confidence listingCompany trend -86.4%
Quick readStrong listing-quality and freshness signals

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

PythonAWSLinuxRest
O
📍 San Francisco, California, United States· Full-time
✓ High-confidence listingCompany trend -86.4%
Quick readStrong listing-quality and freshness signals

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,

PythonAWSRestAI
O
📍 San Francisco, California, United States· Full-time· Remote
✓ Quality checkedCompany trend -86.4%

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

PythonAWSRestAI
O
📍 San Francisco, California, United States· Full-time· Remote
✓ Quality checkedCompany trend -86.4%

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

AWSRestAIC++
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -86.4%

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

AWSRestAIRust
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