Senior Signal Integrity Engineer in United States

NVIDIA’s Silicon Co-Design Group is the team that gets every GPU, SoC, and CPU silicon program from first power-on to high-volume production. We are hiring a Senior Manager to lead our Test, Manufacturability, Reliability & Quality (TMRQ) organization. This is not a coordination role . Your work decides if a product can be built at scale and trusted in the field. These include production test development (SLT, BLT), control run flow, system reliability stress (HTOL), platform- and board-level manufacturing issue closure, and field diagnostic test development. You lead a team of individual contributors and a first-line manager at the layer where silicon, platform, and software collide with manufacturing reality. Decisions you make show up in yield curves, production ramp , and customer escapes. You are the leader the program turns to when a build is stuck, a control run is fallout-heavy, or a field return points back at silicon . The exceptional hire also uses AI deliberately — with demonstrated workflow impact and the judgment to know where it compresses real work and where it introduces risk. What you will be doing: Keep programs moving. Own the technical execution and velocity of SLT, BLT, Board/Chip/Rack CR, and system reliability stress (HTOL) across every GPU, SoC, and CPU silicon program. Close the hardest multi-functional failures. Resolve Vmin and binning escapes, performance shortfalls, and power anomalies by driving root-cause across design, methodology, DFT, ATE, package, software/firmware, and manufacturing — and own the WARs and productized fixes through to confirmation. Give leadership the clarity to act. Convert raw integration signals — CR fallout, BLT/SLT yield, SHTOL/CHTOL data, RMA trends, customer escalations — into decision-ready options that enable executive leadership to act with confidence on POR, QS/PS gates, a

We at NVIDIA seek an Senior Developer Relations, Automated Synthetic Chemistry Science Lead who can coordinate science streams. This role exists at the crossroads of experimental science, optimization, analytical characterization, AI modeling, laboratory automation, and data infrastructure. It demands a practitioner with a background in research who can lead interdisciplinary science teams and accelerate experimentation without compromising scientific quality. What you'll be doing: Coordinate the operating plan across research priorities, technical execution, and program achievements. Convert research objectives into experimental priorities, parameter-space development, campaign planning, and success criteria. Lead research initiatives encompassing synthetic chemistry, catalysis, process chemistry, machine learning, automated systems, and data processing. Build standardized experimental traces capturing successful and unsuccessful outcomes, metadata, quality-control signals, analytical summaries. Guide AI systems for feasibility assessment, outcome prediction, optimization, scope exploration, and campaign orchestration. Integrate automated experimentation, analytical data streams, data curation, model retraining, and campaign decisions into a closed-loop operating model. Establish science-stream governance: build reviews, decision logs, risk and dependency tracking, quality thresholds, and paths for addressing blocking issues. Prepare recurring workstream readouts for program leadership, including scientific progress, critical decisions, cross-team dependencies, resource needs, and unresolved risks. What we need to see: PhD (or equivalent experience) with 10+ years of hands-on experience in experimental science, chemical engineering, material science, robotics, a

NVIDIA is seeking a Senior System Architect: Heterogeneous EDA Systems to solve a complex challenge in accelerated computing: Failure Attribution at Scale. As EDA or equivalent experience workloads scale across thousands of heterogeneous nodes, a single failure can cause massive resource waste. We need an engineer to develop and build an automated framework. This framework will ingest telemetry from CPU and GPU clusters to identify the root cause of job failures in real-time. It will distinguish between hardware faults, infrastructure instability, and software defects. What you'll be doing: Architect Failure Attribution Frameworks: Build a scalable "flight recorder" for EDA jobs that captures high-fidelity state across the CPU, GPU, and Fabric at the moment of failure. Build automated diagnostics that correlate GPU XID errors, PCIe bus failures, and CUDA memory exceptions. Connect these errors with system-level events such as OOM kills or NUMA-related hangs. Distributed Logging & Tracing: Implement low-overhead tracing mechanisms (using tracing tools or custom agents) that provide access to job execution across multi-node Slurm or Kubernetes clusters. Root Cause Automation: Develop heuristics and models based on machine learning to classify failures as "Hardware Fault," "Software Bug," or "Environment Issue." This reduces the Mean Time to Identify (MTTI) for R&D teams. Resiliency Engineering: Work closely with hardware and infrastructure teams to define "signals of impending failure," enabling proactive job migration or check-pointing before a crash occurs. What we need to see: Distributed Systems Mastery: BS, MS, or PhD in Computer Science or Electrical Engineering (or equivalent experience) with 6+ years in systems programming. Experience building automated

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Fraud Data team at Plaid builds the machine learning systems that power Plaid’s fraud detection products, leveraging insights from across Plaid’s network to help identify and stop fraud before it happens. Our team works across the full data science and machine learning lifecycle—from discovering new signals and experimenting with models to deploying and optimizing them in production. We continuously learn from real-world model performance and customer feedback to improve our systems and develop new ways to protect customers and consumers from evolving fraud threats. As a Senior Machine Learning Engineer on Plaid's Fraud Data team, you will develop models that improve fraud detection for our customers. You will identify predictive patterns in Plaid's network data and lead projects from initial experiments through model deployment and ongoing improvement. Investigate fraud patterns and model errors to identify new signals, improve detection, and expand coverage across customers and use cases. Develop training datasets and predictive features, addressing challenges such as incomplete labels, class imbalance, data leakage, and changing fraud behavior. Design, train, and tune model

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. We are the Fraud Data team within Plaid's Fraud organization. We leverage relationships and activity across Plaid’s network to develop machine learning models that help customers detect and prevent fraud while minimizing friction for legitimate users. Our team owns the full model lifecycle, from data processing and experimentation to feature pipelines, model serving, and monitoring. In this research role, you’ll partner closely with Machine Learning Engineers and Data Scientists to uncover new signals, explore and evaluate innovative modeling approaches, and translate promising research into production-ready solutions that strengthen fraud detection across Plaid’s network. As a Senior Research Scientist, you will lead applied research to develop next-generation fraud detection models across relational graphs, sequential events, images, and video data. You’ll design rigorous experiments and evaluation methodologies that reflect real-world fraud dynamics, while exploring state-of-the-art approaches such as Graph Neural Networks and Transformer-based foundation models. In close partnership with Machine Learning Engineers, you’ll translate promising research into production-ready solu

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role At Ramp, people are the single biggest lever on our trajectory, and the bar for who joins this team gets higher every quarter, not lower. We're hiring a Recruiter who treats recruiting as a research discipline as much as a relationship one: someone who can map a market, identify the operators who'll outperform their peers, and run a full-cycle process that wins them. You'll own end-to-end hiring across Sales and GTM functions, from first conversation through offer close, and partner with GTM leadership to translate ambitious hiring plans into real teams. The recruiters who do this best at Ramp combine craft on the front end (research, identification, calibration) with execution on the back end (closing, candidate experience, pipeline discipline). We're looking for both. What You'll Do Use AI and research to find top talent. You'll build target lists of high performers at peer and aspirational companies using LinkedIn Recruiter, Sales Navigator, Gong signals, internal data, and AI tools like Claude. We expect AI to be part of your dail

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role The Senior Lifecycle Marketing Manager is responsible for strategizing, executing, and optimizing data-driven lifecycle communications for GitLab’s product-led and self-service audiences. This role collaborates with Product Growth, SMB Sales, Marketing Ops, Data, Product Marketing, Campaigns, and regional teams to plan and prioritize programs that engage free, trial, self-managed, and self-service users and guide them toward activation, conversion, and revenue growth. They will focus on leveraging audience data, product signals, cross-team collaboration, and continuous testing to improve lifecycle

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As a Senior Threat Investigator on the Safety Investigations team, you will help lead Roblox’s deep-dive investigative capability for the most severe, complex, and externally significant safety matters. You will conduct actor-centric and network-centric investigations, proactively identify sophisticated threat actors and abuse patterns, and develop high-quality investigative work product that supports internal decision-making and, where appropriate, external law-enforcement engagement. The ideal candidate will have an exceptional investigations background, strong analytical tradecraft, and a demonstrated ability to connect fragmented internal and external signals into clear, defensible investigative findings. They will be an innovative self-starter, a collaborative partner across functions, and someone motivated by Roblox’s mission of connecting a billion people with optimism and civility. Through your work, you will become an expert in Roblox’s internal and external safety practices, advance our investigative capabilities and playbooks, and work across a variety of systems and data sources to surface, analyze, and ultimately disrupt high-risk actors, networks, and behaviors. Please note: T

As a Senior Platform Product Manager focused on AI SDLC Trusted Throughput, you will define and drive the product strategy for enabling safe, reliable software delivery at AI-native scale across Datadog’s Internal Developer Platform. As AI accelerates development velocity and system complexity, you will help evolve SDLC systems from human-supervised workflows to platforms with built-in safety, observability, and correctness guarantees. You will partner closely with engineering, security, and developer platform teams to improve deployment reliability, operational visibility, and governance while enabling both engineers and AI agents to move quickly with confidence. This role offers the opportunity to shape foundational developer infrastructure and influence how AI-powered software delivery operates across Datadog. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Own the product strategy, roadmap, and execution for AI-native SDLC throughput and reliability initiatives across Datadog’s Internal Developer Platform Define and drive platform outcomes aligned to DORA metrics, balancing deployment velocity with reliability, change failure reduction, and operational safety Partner with engineering, infrastructure, security, and developer experience teams to build automated validation, auditability, and risk-scoring capabilities into deployment workflows Deliver actionable SDLC observability and diagnostic capabilities that connect executive-level metrics to operational signals across the software delivery lifecycle Drive systems that monitor and validate AI-generated or AI-attributed changes to ensure correctness, compliance, and trustworthy automation Serve as a cross-functional product leader across SDLC Foundations, Security Engineering, and compl

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Difference You Will Make: Airbnb is entering a new era—reimagining how fraud, safety, and quality are measured, protected, and elevated across the digital landscape. Reporting to the Director of Advanced Analytics, Fraud & Safety, you will lead a dispersed team of ~8 advanced analysts tasked with turning safety measurement into governed, self-serve decision systems for Policy, Ops, Legal, Product, and Engineering. You will be a pivotal leader safeguarding Airbnb’s global community. You’ll steer a multidisciplinary team that designs, delivers, and scales state-of-the-art analytics for: Safety (physical & digital) Connected-account & circumvention detection Privacy protection & risk management This role isn’t just about reporting what happened; it’s about building the systems that help Airbnb see around corners. You will democratize data access, build always-on scenario simulators for fraud and safety, and turn incident impacts into seamless signals for continuous improvement. Your insights and systems will empower every stakeholder—from legal to operations, policy to product—to make bold, data-driven, and context-aware decisions in real time. A Typical Day: Own end-to-end analytical workflows for platform safety controls: data ingestion, feature engineering, modeling, experimentation, and visualization. A core mandate is to co-own and drive the enterprise-wide “Safety Single Source of Truth” (SSoT) strategy —a unified, structured data asset and taxonomy that underpins decision-making across Product, Operations, Policy, and Legal. Ensure metrics are future-proof, privacy-compliant, and g

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: The Relevance and Personalization team at Airbnb is responsible for search and recommendation across the entire Airbnb digital platform. In this role you'll focus on query intelligence, the front door of search working on critical, impactful projects that turn what a guest types, taps, or says into a precise understanding of their intent, spanning autocomplete and smart compose, query tagging, query expansion, and intent modeling across Stays, Experiences, and Services. The Difference You Will Make: Query understanding is where every search begins, and it directly shapes retrieval, ranking, and ultimately the perfect match between guests and hosts. We build cutting-edge AI technologies across the end-to-end search ranking product stack w.r.t. data pipelines, feature and model innovations, serving and experimentation efficiency, leveraging rich signals from various types of data (structured, sequential, image, text, etc) and increasingly large language models at Airbnb. You'll build the models that parse free-form and natural-language multimodal queries, extract entities and location context, classify intent, and anticipate what guests want before they finish typing. We collaborate closely with teams across Airbnb to develop the ranking solutions and support a healthy marketplace for hosts and guests to further Airbnb's mission of creating a world where people can Belong Anywhere. Some past publications from the team can be found here: https://sites.google.com/view/airbnb-relevance-publications/home A Typical Day: Work with large scale structured and unstructured data, build an

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: The Senior Principal, Competitive Intelligence will report to the Director, Product & Performance within Strategic Finance & Analytics. Airbnb is looking for a unique individual that can blend art and science to evaluate our evolving competitive landscape. This team is responsible for understanding the market across geographics and product offerings, building evaluation criteria and metrics, and delivering clear insights to leaders across the company. The Difference You Will Make: The individual will serve as the company's go-to authority on the competitive landscape, including current and future competitors, adjacent marketplaces, the travel industry at large and macroeconomic trends. They will partner with technical and business operating teams to synthesize competitive signals into clear, actionable narratives that inform executive decision-making at the highest levels of the company. The ideal candidate brings a combination of sharp analytical instincts, business acumen, and the ability to distill complex information into crisp executive-ready stories. They are a self-starter who is comfortable operating with ambiguity, thrives in a fast-paced environment, and relishes the opportunity to own a critical capability from end to end. This person will have a high degree of visibility with senior leadership, including Executive and VP leaders across Finance, Product, Marketing and Business functions. A Typical Day: Competitive Monitoring: Develop and manage regular reporting to review key metrics across marketplace and product; track developing news and indus

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: AI and ML are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing, we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb. The Core ML team is responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting Generative AI technologies to enable an intelligent, scalable, and exceptional service experience. The team develops and enhances AI models, ML services, and tools including LLM fine-tuning and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning, and guardrails for a wide range of applications at Airbnb. The richness of Airbnb's data, the complexity of its marketplace, and the variety innate in our product mean that we need to operate at the state of the art of AI practice. We are committed to long-term innovation to solve complex problems, and to do that we need experienced ML ​​The Difference You Will Make: In this Senior Staff role, you will set technical direction and lead execution for ML evaluation and the end-to-end data flywheel powering CSxAI products (e.g., assistive agents, issue resolution, and tooling). Your work will define how we measure quality, how we turn feedback into learning signals, and how we continuously improve models and products safely and efficiently. You will partner closely with product, engineering, design, operations to build evaluation systems that are trusted, scalable, and actionable - connecting offline metrics to online outcomes. A Typical Day: Define evaluation strategy and suc

About the Team The B2B Marketing team is responsible for helping businesses understand, adopt, and get value from OpenAI’s products. B2B marketing is a major and growing priority for OpenAI as we scale our work with companies, developers, and institutions around the world. About the Role Within B2B Marketing, Demand Generation builds the integrated, full-funnel engine that connects audience insights, content, field and digital experiences, paid media, lifecycle, and sales follow-through to qualified pipeline. We partner closely with Sales, Partnerships, Product Marketing, Communications, Creative, Web, RevOps, Analytics, and regional teams to create a cohesive customer experience and scale what works. We’re looking for a Senior Marketing Strategist to lead paid and emerging demand-channel strategy for OpenAI’s B2B business. You’ll own the B2B audience, channel, offer, partner, and measurement strategy, translating pipeline goals into clear briefs and investment recommendations. You’ll partner closely with Performance Marketing, which owns hands-on media execution, while informing audience strategy, campaign priorities, experimentation, and downstream performance decisions. You’ll also build our approach to content syndication and third-party demand media partnerships. In this role, you will: Owning the B2B paid and emerging-channel demand strategy across paid search, paid social, display and retargeting, content syndication, third-party demand media partnerships, sponsorships, review platforms, and selected emerging channels. Translating pipeline goals into audience and channel strategies, including ICP and segment priorities, buying groups, intent signals, channel roles, forecast assumptions, budget recommendations, campaign architecture, and a rolling experimentation roadmap. Partnering closely with Performance Marketing to define B2B audience, campaign, offer, creative, landing-page, conversion, and measurement requirements, while Performance Marketing owns media

About the Team The B2B Marketing team is responsible for helping businesses understand, adopt, and get value from OpenAI’s products. B2B marketing is a major and growing priority for OpenAI as we scale our work with companies, developers, and institutions around the world. Within B2B Marketing, Demand Generation builds the integrated, full-funnel engine that connects audience insights, content, field and digital experiences, paid media, lifecycle, and sales follow-through to qualified pipeline. We partner closely with Sales, Partnerships, Product Marketing, Communications, Creative, Web, RevOps, Analytics, and regional teams to create a cohesive customer experience and scale what works. About the Role We’re looking for a Senior ABM Strategist to build and lead the operating model for OpenAI’s highest-priority enterprise accounts. You’ll translate commercial priorities into focused 1:1 and 1 account programs, align Marketing and Sales around shared account plans, and orchestrate buying-group engagement across channels. This is a hands-on builder role for someone who can define the strategy, establish the system, and work directly with cross-functional partners to move strategic accounts toward qualified pipeline and revenue. In this role, you will: Own the enterprise ABM strategy, including account selection, tiering, objectives, program architecture, investment decisions, and performance recommendations. Partner with Sales, SDR, and RevOps to build shared account plans, map buying groups, identify whitespace, define engagement plays, and establish clear follow-up ownership. Design and execute 1:1 and 1 programs across content, paid media, executive engagement, events and webinars, web experiences, outbound coordination, and other relevant channels. Use intent, product, firmographic, engagement, and seller signals to determine when and how to activate priority accounts. Translate account and buyer insights into personalization strategies, offers, messaging, and conte