Signal Integrity Engineer in United States

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

NVIDIA's accelerated computing platforms move data at speeds that push the limits of what silicon and physics allow. Whether a high-speed interface trains reliably, maintains accurate margins, and survives every platform topology it will ever see is a question we answer ourselves. This role does that work. The Silicon Co-Design Group leads the boundary between what was designed and what was built. When a GPU, CPU, or SoC ships with interfaces that work at scale, this team is the reason. Most engineers debug within a layer. You will own the full stack. When an interface fails to train, the link margin is unexpectedly tight, or a customer reports a critical silicon issue, you trace the problem through protocol behavior, signal integrity, firmware, platform topology, and silicon marginalities. You then confirm that the fix works. Your methodology shapes how NVIDIA validates high-speed interfaces across generations. Your decisions affect yield, production ramp, and field quality. This is not a coordination role. The engineers who do it well hold protocol depth and system breadth simultaneously, never lose the thread across hardware, firmware, and software, and have the judgment to know when to go deeper and when to act. They are rare. Should that describe you, read on. What you'll be doing: Own post-silicon bring-up, characterization, validation, and debug of PCIe, NVLink, C2C, and other HSIO interfaces across NVIDIA GPUs, CPUs, and SoCs from first power-on through production readiness. Close the hardest failures. Drive root cause across protocol behavior, signal integrity, firmware and driver interactions, platform topology, and silicon marginalities and own every fix through to confirmation. Define validation strategy. Set test coverage, debug priorities, margining methodology, and stress criteria f

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 Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . We’re hiring a Staff Machine Learning Engineer to help drive the future of merchant presence and shopping experiences on Pinterest. This role sits on the Merchant team and focuses on building AI/ML systems (including LLMs) that identify, understand, and surface relevant, high-quality merchants across segments—so Pinners can discover new brands with greater confidence and consideration, and merchants can reach new, diverse audiences. In this role, you’ll lead LLM-first, evaluation-driven initiatives—near-term focused on agentic workflows, measurement, and operational rigor that strengthen Merchant Integrity and Business Integrity. Longer term, you’ll help advance core relevance capabilities such as merchant/brand affinity modeling and related signals that improve shopping discovery across Pinterest. You’ll partner closely with Product Managers, E

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

Discord has a highly engaged community of millions of daily active users who use the platform for many different reasons, but there’s one thing that nearly everyone does: play video games. Discord plays a uniquely important role in the future of gaming, and we are focused on making it easier and more fun for people to hang out before, during, and after playing games. Discord exists to give people the power to create space to find belonging — to talk regularly with the people they care about and build genuine relationships with friends and communities close to home or around the world. We're looking for an Analytics Manager to lead our Scaled Abuse Countermeasures and Research (SCAR) team — the team that safeguards Discord’s platform integrity. SCAR detects, analyzes, and disrupts high-volume threats through a combination of automated systems, deep research, and active incident response. This role reports to the Head of Safety Intelligence and Automation. What You'll Be Doing Lead and mentor a team of data analysts, scientists, and researchers who investigate active threats, identify platform abuse vectors, and uncover adversarial patterns. Define a strategic roadmap that prioritizes and disrupts the highest impact abuse operations through structured research, rigorous analyses, and live experimentation. Collaborate closely with the safety machine learning team to improve models by identifying the threat signals that translate into long-term, automated countermeasures. Partner cross-functionally with Product, Engineering, Data Science, Policy, Legal, and Revenue, influencing safety-by-design decisions upstream of abuse. Influence capacity toward high-impact infrastructure, such as automated rule engines, ML models, or agent moderation tools. What you should have 2+ years of people management experience leading technical teams, including engineers, data scientists, analysts, applied researchers, or equivalent. 4+ years of experience working in a Trust & Safety dom

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

About the Team The Systems Integration team is responsible for building the infrastructure, tooling, and validation systems that ensure our device software is reliable, testable, and ready to ship. We design and maintain automated test frameworks, hardware-in-the-loop labs, and release pipelines that keep quality signals trustworthy and enable rapid, safe product launches. Our work spans developer tools, automation, systems integration, and cross-team collaboration to ensure every release meets the highest standards. About the Role As a Software Engineer, Quality and Developer Tools , you will build and own the systems that validate our device software—from test frameworks and regression infrastructure to hardware-in-the-loop labs and release gates. You’ll design the tooling and automation that keep quality signals trustworthy, integrate them into CI/CD, and make it easy for engineers and QA vendor technicians to execute reliable, repeatable workflows. We’re looking for engineers with deep experience in software quality, automation, developer tooling, and hardware-software integration who thrive on building scalable, reliable systems for validation and release readiness. This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In this role, you will: Test infrastructure & frameworks: Design, implement, and maintain a unified test framework for device software across unit, integration, system, and end-to-end testing, with reproducible runs and integrations with GitHub, Linear, and Slack. CI/CD integration & releases: Integrate test suites with Buildkite, enforce promotion criteria for staging and production, auto-file regressions, and publish traceable artifacts and release notes. Hardware-in-the-loop lab design & orchestration: Plan and bring up racks, power and networking systems, and orchestration for device testing; support automated flashing, provisioning