Signal Integrity Engineer in San Francisco

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 signal integrity (SI) system design engineers who have a deep expertise in the SI area, and hold strong system level design knowledge 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 system signal integrity (SI) design for AI supercomputer product in the data center application. Collaborate with chip, package, boards, rack and system engineers, design partners to drive system SI design and develop innovative interconnect and high-speed technologies Identify and evaluate new technologies and methodologies to improve signal and power integrity in product design, and contribute to the development of new products and technology by providing expertise in signal integrity Perform simulation and modeling to identify and troubleshoot signal integrity issues Lead system interconnect design, bring up and qualification As the scope of the role and team grows, understand and influence roadmaps for hardware partners for our datacenter networks, racks, and buildings. You might thrive in this role if you: Have at least 10 years of industry experience, including experience design hardware system and SerDes testing for data center applications Have a strong bias toward action, and won’t take no for an answer. Have experience and good knowledge of system design experience in the SI areas, from chip, SerDes, board, rack level Have ex

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

What you’ll do Act as the in-house electrical lead for Midjourney Medical: own the electrical architecture of the scanner and the technical direction for all board-level design. Own complex board design end-to-end: architecture, schematic capture, layout (high-speed digital, analog/mixed-signal, power), DFM/DFT, fabrication and assembly vendor management, bring-up, and revision control. Write firmware for embedded targets (MCU/SoC): drivers, real-time control loops, safety-relevant logic, bootloaders, and field update paths. Audit and update HDL (FPGA) code for high-throughput data acquisition, timing/synchronization, triggering, and pre-processing of ultrasound and sensor data streams. Define electrical interfaces and data contracts with software, recon/ML and mechanical teams: timing budgets, clocking/sync, signal integrity, connectors/harnessing, and failure modes. Establish electrical engineering rigor: design reviews, schematic/layout review checklists, bring-up procedures, test fixtures, and documentation suitable for a regulated medical device program (DHF, traceability, change control). Mentor and grow the electrical function; select and manage external design partners where leverage is high. What we’re looking for Deep experience designing complex boards from blank page to stable revision, including high-speed digital and analog/mixed-signal domains. Strong schematic and layout skills (Altium/KiCad or equivalent) with real signal integrity, power integrity, grounding, and EMI/EMC instincts. Solid embedded firmware background in C/C++ (and Python for tooling): peripherals, DMA, interrupts, real-time constraints, and debugging on hardware. Practical HDL experience (VHDL/Verilog/SystemVerilog) for data acquisition, timing, and streaming interfaces. Track record of owning bring-up and debug on real hardware: scopes, logic analyzers, and disciplined root-cause analysis. Technical leadership: clear trade-offs, strong written documentation, and the ability to set

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 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

About the Team OpenAI’s mission is to ensure the responsible and widespread adoption of artificial intelligence. In support of that mission, the Ads Solutions team partners closely with advertisers to deeply understand their businesses and needs, helping inform the development of products and solutions that drive meaningful revenue growth and long-term success on the platform—while maintaining strong standards for user trust and platform integrity. About the Role We’re looking for an Ads Solutions Engineer to partner with advertisers and agencies throughout the pre-sales and growth lifecycle, helping them successfully evaluate, launch, and scale on OpenAI’s advertising platform. You will serve as the technical expert in the sales process, translating advertiser objectives into scalable technical solutions across measurement, integrations, data activation, and campaign execution. This role sits at the intersection of sales, product, and engineering. You’ll work closely with Client Partners, Customer Success Managers, Product, Engineering, Policy, and Operations teams to remove technical blockers, accelerate revenue growth, and shape the future of OpenAI’s ads platform. This role is based in our San Francisco HQ and we offer generous relocation support for new hires. In this role, you will: Partner with Client Partners during the sales cycle to provide technical expertise that unlocks new business and accelerates deal closure. Lead technical discovery with advertisers and agencies to understand data flows, martech stack, measurement requirements, and activation goals. Design and recommend implementation approaches for pixels, APIs, server-to-server integrations, identity solutions, offline conversions, and measurement frameworks. Guide advertisers through onboarding and launch readiness, ensuring successful setup of tracking, attribution, audience signals, and reporting. Troubleshoot technical issues related to implementation, signal quality, delivery, and measurement

About the Team OpenAI’s mission is to ensure the responsible and widespread adoption of artificial intelligence. In support of that mission, the Ads Solutions team partners closely with advertisers to deeply understand their businesses and needs, helping inform the development of products and solutions that drive meaningful revenue growth and long-term success on the platform—while maintaining strong standards for user trust and platform integrity. About the Role We’re looking for an Ads Solutions Engineer to partner with advertisers and agencies throughout the pre-sales and growth lifecycle, helping them successfully evaluate, launch, and scale on OpenAI’s advertising platform. You will serve as the technical expert in the sales process, translating advertiser objectives into scalable technical solutions across measurement, integrations, data activation, and campaign execution. This role sits at the intersection of sales, product, and engineering. You’ll work closely with Client Partners, Customer Success Managers, Product, Engineering, Policy, and Operations teams to remove technical blockers, accelerate revenue growth, and shape the future of OpenAI’s ads platform. This role is based in our San Francisco HQ and we offer generous relocation support for new hires. In this role, you will: Partner with Client Partners during the sales cycle to provide technical expertise that unlocks new business and accelerates deal closure. Lead technical discovery with advertisers and agencies to understand data flows, martech stack, measurement requirements, and activation goals. Design and recommend implementation approaches for pixels, APIs, server-to-server integrations, identity solutions, offline conversions, and measurement frameworks. Guide advertisers through onboarding and launch readiness, ensuring successful setup of tracking, attribution, audience signals, and reporting. Troubleshoot technical issues related to implementation, signal quality, delivery, and measurement

About the Team The Intelligence and Investigations team seeks to rapidly detect and disrupt abuse in AI technologies to ensure their safe use. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits all of humanity. About the Role As an Intelligence Systems Engineer, you’ll be focused on advancing our Intelligence & Investigations efforts at OpenAI, ensuring the safe and responsible use of AI across our products and services. We are seeking a self-starter to prototype, develop, and maintain new tools and processes that integrate OpenAI’s models and infrastructure to enable internal teams to make sense of large, open-domain datasets, fight abuse, and inform high-stakes decisions. You will be a crucial technical bridge between our data scientists and subject matter experts and technical teams like Platform Integrity, Safety Systems, and Research by leading the development of innovative tools and processes that bolster goals in scaled collections, investigations, and analysis. The ideal candidate has strong analytical and data skills, with a background in both prototyping and building scalable systems that can swiftly detect emerging threats, process vast amounts of information, and deliver insights to stakeholders. We value professionals with outstanding communication skills, a commitment to continuous learning, and who are dedicated to promoting the responsible use of AI. 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: Prototype, build, and maintain at-scale intelligence systems that detect, triage, and monitor targeted signals from both open-source and internal data Analyze requirements and deliver end-to-end solutions that address

About the role We’re looking for an engineering manager to lead a team building software systems that detect and prevent harmful misuse of frontier AI models—before incidents occur. This is a builder’s role: you’ll lead engineers shipping production services, detection pipelines, and mitigation mechanisms that protect frontier model integrity and reduce high-severity misuse risk. While this work intersects with frontier model development, security and risk, we’re explicitly seeking someone with a software engineering foundation who is comfortable building reliable systems that can operate at billions of users scale. In this role you will: Lead a team of software engineers building detection + mitigation systems for frontier model misuse, with an emphasis on model IP protection / distillation detection and emerging risk surfaces from autonomous agents. Set the technical roadmap and execution strategy: prioritize, design, ship, iterate, measure impact. Build production systems: services, pipelines, tooling, instrumentation, and automation that scale with frontier model usage. Partner deeply with Research and Product to translate evolving model capabilities into concrete tests, signals, and mitigations that can be deployed at scale. Drive strong engineering fundamentals: architecture, reliability, monitoring, performance, and operational excellence. Hire and grow an exceptional team across backend, data systems, and applied ML engineering domains as needed. Anticipate what breaks at scale as agentic workflows become more capable. You might thrive in this role if you: Experience building systems in adversarial, fast-evolving environments Are comfortable with ambiguity and novelty Have experience adjacent to security (e.g., abuse prevention, fraud, integrity, platform defense, auth/identity, malware/spam, adversarial environments) Communicate clearly and build trust quickly with senior stakeholders—pragmatic, collaborative, and calm under scrutiny. Significant experience

About the Team The Applied team brings OpenAI’s technology to the world through products used by hundreds of millions of people and by developers and businesses building on our APIs. We work across research, engineering, product, policy, safety, and operations to deploy frontier AI systems responsibly and safely. The Trust & Safety Data Engineering team builds the data foundations that help OpenAI understand, detect, investigate, and mitigate abuse and safety risks across our products. We partner with Integrity, Investigations, Safety Systems, Product Policy, Privacy, Data Science, Engineering, and Data Platform to create reliable, privacy-safe datasets and pipelines for fraud and abuse detection, enforcement workflows, safety measurement, ML feature generation, launch readiness, and transparency reporting. About the Role We are hiring a Technical Lead Manager to lead and grow the Trust & Safety Data Engineering team. This is a hands-on leadership role for someone who can set strategy, shape data architecture, align senior stakeholders, coach engineers, and drive execution on high-impact data systems. You will help turn fragmented launch and incident support into durable, reusable, privacy-safe data foundations that Trust & Safety teams can rely on. The systems your team builds will help OpenAI detect risk, investigate abuse, power operational workflows, develop and evaluate safety models, measure interventions, support product launches, and report accurately on platform integrity. In This Role, You Will Lead and grow a high-performing Trust & Safety Data Engineering team. Define the roadmap and technical strategy for Trust & Safety data systems. Build canonical, privacy-safe datasets and pipelines for abuse detection, fraud detection, risk signals, enforcement, scaled review, transparency reporting, and safety monitoring. Create reusable foundations for Trust & Safety model development, including features, labels, training data, backtesting,

About the Team At OpenAI, Trust & Safety Operations is central to protecting OpenAI’s platform, customers, and the public from abuse. We partner closely with Product, Engineering, Legal, Policy and Go To Market teams to identify emerging risks, build and mature enforcement systems, and ensure high-integrity operations while delivering a great user experience at scale. We’re building the Monetization Trust & Safety Operations team to ensure OpenAI can grow advertising in a way that is safe, trusted, and sustainable—for users, advertisers, and the business. This team sits at the intersection of operational scale, product risk, and rapid revenue growth, designing systems and operations that enable ads to scale without compromising user trust or safety. It’s critical to us that our Ads product be built in a way that corresponds to our Ads principles , and this team is key to that. About the Role We’re looking for a senior operator with strong analytical instincts to help build and scale Monetization Trust & Safety Operations at OpenAI. In this role, you’ll flex across the team’s highest-priority data and operational needs—from reporting and dashboard insights to budget and capacity planning, project-based analysis, and data automation —while partnering closely with Product, Policy, Engineering, Legal, Go To Market, and Data Science and Data Engineering teams. This role sits at the intersection of strategy, execution, and data: you’ll define ambiguous problems, query and validate data, build decision-support systems, and translate operational signals into clear recommendations and scalable, AI-first solutions. You should be comfortable moving from a high-level question to a rigorous analysis, a useful dashboard, an automated workflow, or a durable operating mechanism. As OpenAI introduces new revenue-generating formats and partnerships, you’ll help the team understand where risks, capacity constraints, quality gaps, and opportunities are emerging. You’ll brin

About the Team At OpenAI, Trust & Safety Operations is central to protecting OpenAI’s platform, customers, and the public from abuse. We partner closely with Product, Engineering, Legal, Policy and Go To Market teams to identify emerging risks, build and mature enforcement systems, and ensure high-integrity operations while delivering a great user experience at scale. We’re building the Monetization Trust & Safety Operations team to ensure OpenAI can grow advertising in a way that is safe, trusted, and sustainable—for users, advertisers, and the business. This team sits at the intersection of operational scale, product risk, and rapid revenue growth, designing systems and operations that enable ads to scale without compromising user trust or safety. It’s critical to us that our Ads product be built in a way that corresponds to our Ads principles , and this team is key to that. About the Role We’re looking for a senior operator to help build and scale Monetization Trust & Safety Operations at OpenAI. In this role, you’ll own critical Ads T&S workstreams from problem framing through scaled operation, partnering closely with Product, Policy, Engineering, Legal, and Go To Market to turn ambiguous priorities into durable operating models. This role sits at the intersection of strategy and execution: you’ll define scope, align owners, manage milestones and risks, resolve dependencies, and build the workflows, decision structures, and operating mechanisms that allow Ads Trust & Safety to scale. You’ll move between standing up new programs, stabilizing existing workflows, and handing off durable ownership as priorities evolve. As OpenAI introduces new revenue-generating formats and partnerships, you’ll bring structure to complex initiatives that balance user safety, advertiser experience, and business growth. You’ll use data and frontline signals to identify bottlenecks, quality gaps, capacity needs, and high-leverage interventions, and communicate clear

About the Team Critical Harm Operations sits within User Safety & Risk Operations and builds enforcement systems for Frontier Risk and Material Harm that are accurate, fast, defensible, and built to scale. We turn policy intent into operational readiness, review standards, quality systems, escalation paths, automation guardrails, and durable cross-functional operating models. About the Role We are looking for an exceptional Program Manager to help build durable operating systems and run some of OpenAI’s most complex safety operations. The core need is a high-agency operator who can take an ambiguous problem, create the right structure, align cross-functional partners, and drive the work through execution. This role will move across Critical Harm priorities as needs evolve. You may step into operationalizing national security or violent-activities workflows, support wellbeing and Frontier Risk initiatives, or help scale programs such as Trusted Access. Deep domain expertise is helpful but not required; the strongest candidates will learn quickly, exercise excellent judgment, and make complex programs move. In this role, you will: Lead strategic operational builds across priority workflows from problem statement to implemented operating model, including scope, owners, milestones, risks, success measures, and execution cadence. Translate policy, safety, technical, legal, and operational constraints into workflows, requirements, playbooks, escalation paths, and decision-making structures that teams can execute. Coordinate with User Ops leadership, Product Policy, Integrity, Safety Systems, i2, Legal, Product, Engineering, Support, vendors, and other partners to resolve dependencies and keep critical work moving. Move in and out of workflows as priorities shift—standing up new programs, stabilizing operations, improving handoffs, and transitioning durable ownership to the right team. Use operational data and frontline signals to identify bottlenecks, quality gaps, ca

About the Team The Hardware Health and Observability team owns the end-to-end health lifecycle of OpenAI’s global compute fleet. Our mission is to maximize healthy, usable compute across accelerator vendors, generations, cloud providers, and regions through reliable health signals, automated remediation, and scalable operational tooling. We build the systems that observe, detect, remediate, and verify hardware issues across GPUs, CPUs, networking, and platform infrastructure, enabling frontier model training and inference workloads to run reliably at hyperscale. We are the last line of defense for the success of OAI’s production and research workloads. About the Role On the Hardware Health and Observability team, you’ll build critical infrastructure that keeps OpenAI’s largest compute clusters healthy and operational at scale. Even small numbers of unhealthy systems can impact large-scale training and inference workloads. This team focuses on minimizing downtime, improving fleet efficiency, and ensuring compute resources remain continuously available to researchers and product teams. Engineers on this team own problems end-to-end, from defining health signals and debugging failures to building automated remediation systems that operate across millions of GPUs globally. In this role, you will: Define and maintain health signals across GPUs, CPUs, networking, and platform infrastructure. Build and evolve health checks that detect, remediate, and verify failures at scale. Ensure critical health checks execute with minimal latency to maximize workload uptime. Investigate hardware failures and system-level issues across large-scale compute environments. Own node lifecycle workflows including drain, quarantine, repair, RMA, and return-to-service processes. Build automation and tooling that enables global cluster management with minimal manual intervention. Partner with workload, reliability, and provider teams to integrate health signals into training and inference system

About the Team The Future of Computing Research team is an applied research team within OpenAI’s Consumer Devices group. We study how AI systems perceive people and their surroundings, and we turn that research into capabilities for future products. Our work spans machine learning, sensing, and hardware, with a focus on building systems that work beyond controlled environments. About the Role We’re looking for a machine learning engineer to help shape how future AI systems understand the physical world and the people in it. The role focuses on multimodal perception and authentication, bringing together signals from cameras, microphones, and other sensors. You’ll work with specialized perception models and larger multimodal models, and partner with hardware, firmware, software, and product teams to bring new research into real-world systems. This role is based in San Francisco. We work in the office three days per week and offer relocation assistance. In this role, you will: Research and develop multimodal perception and authentication methods across visual, audio, and other sensing signals. Explore how specialized perception models and larger multimodal models can work together. Design data, training, and evaluation approaches that improve performance in real-world conditions. Study model behavior, robustness, and failure modes across sensing, data, and deployment environments. Integrate and validate new capabilities in real-time or resource-constrained systems. Work with hardware, firmware, software, and product teams to turn research into working systems. You might thrive in this role if you: Have a strong background in computer vision, audio or speech machine learning, multimodal learning, or sensing. Have experience developing specialized machine learning models, larger multimodal models, or both. Have brought research ideas into practical systems, prototypes, or products. Know how to design experiments, build evaluations, and investigate model behavior. Have wo