Signal And Growth Insights Manager in United States

About the Team The Product Explorations team is a small, high-ownership product exploration group focused on turning new model capabilities into impactful user experiences. We operate across Applied and Research, working closely with product, engineering, design, and research partners to identify promising opportunities, prototype quickly, validate ideas, and determine which efforts should scale into larger product investments. Our objective is broad: discover and build experiences that can meaningfully improve user engagement, product impact, and revenue across OpenAI’s products. We move quickly, follow strong product signals, and take ideas from early exploration to meaningful user impact. About the Role We are looking for product-minded full stack engineers to join the Product Explorations team and drive high-impact, net-new product explorations. In this role, you will independently identify promising opportunities, move quickly from idea to prototype, and work across teams to validate and launch new experiences. You will operate with a high degree of autonomy, use strong product intuition, and make thoughtful decisions in ambiguous environments. You may work on a new ChatGPT experience one week, explore a new model capability the next, and partner with Research or Applied teams to turn the strongest ideas into scalable products. This role is a strong fit for someone who enjoys building from scratch, iterating quickly, and working on projects where the path forward is not always obvious. In this role, you will: Identify and pursue high-leverage product and technical opportunities across OpenAI’s products Move quickly from idea to prototype, validation, launch, and iteration Build full stack product experiences that unlock value from new model capabilities Work closely with Research, Applied, product, design, data science, and engineering partners Use user feedback, product signals, and experimentation to determine which ideas should scale Drive alignment across t

NVIDIA has transformed computer graphics, PC gaming, and accelerated computing for more than 25 years through exceptional technology and the people who build it. In semiconductor manufacturing, our role is to enable the ecosystem, not compete within it. We partner with fabs, equipment manufacturers, and software providers to make inspection, metrology, and manufacturing intelligence dramatically faster on the NVIDIA platform. Our team builds the software that makes this possible: models, adaptation and evaluation workflows, and deployable inference capabilities that partners integrate into their own tools. We work in environments where labeled data is limited and proprietary, distributions shift across tools and fabs, production budgets are tight, and software must operate inside air-gapped facilities. We’re seeking a Principal Systems Software Engineer for Semiconductor Inspection in Santa Clara. This is a hands-on architect role: you will define the approach, build it, evaluate it, and demonstrate the results. You will work across computer vision, time-series modeling, multimodal AI, anomaly detection, model adaptation, evaluation, and production inference. Success means technology that a fab or equipment vendor can integrate, operate, and trust—not only a successful internal demonstration. What you’ll be doing: Define and prototype AI system architectures spanning optical and e-beam inspection, wafer and mask inspection, metrology, defect review, equipment signals, and process data. Advance world foundation model capabilities for semiconductor manufacturing, including vision, time-series and multimodal representation learning, model adaptation, domain transfer, and data-scarce defect understanding. Develop workflows for defect detection, classification, localization, segmentation, nuisance filtering, ADC, AD

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 ABOUT THE ROLE We are hiring the next generation of product managers. AI has collapsed the work that used to sit between an idea and a working version of it, and for the first time, PMs can be true builders. The PMs who win in this era do not manage the work. They build the product, every day, with their own hands. A Staff Product Manager operates and drives vision across product areas. You own a problem space that spans multiple surfaces, or one so foundational that getting it right shapes how everything else at ClickUp works. You still build. The strategy is sharper because you are prototyping the cross-cutting workflow yourself, reading data wherever it shows up, and sitting on customer calls that span the whole problem. You scale impact by inventing leverage that other PMs adopt, wiring up AI workflows that keep you current on more signals than any one person could manually track. The scope is wide on purpose, and you find new ways to cover it. KEY RESPONSIBILITIES Define and own a cross-functional problem space or a foundational platform area whose quality shapes outcomes across multiple product surfaces. Drive strategic alignment across product areas. Identify the decisions that unblock the most work and make them. Synthesize signals from customer calls, data, support trends, and partner feedback across your entire scope, not just your immediate surface. Prototype cross-cutting workflows and concepts yourself. The strategy is more credible when you have already tested it. Identify leverage and share it. Build AI workflows, frameworks, and patterns that other PMs on the team can adopt. Mentor and

At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 40,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America, Europe, and Australia, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. As Linear moves upmarket, the gap between deal close and successful enterprise rollout has become our most important surface area. We're hiring an Implementation Manager to own that gap. You will be the single point of accountability from signed contract through successful go-live, coordinating across CSM, Solutions Engineering, Customer Education, Sales, and the customer's own teams to make every enterprise rollout repeatable, on time, and high quality. Location & work mode Linear is a remote-first company, with optional co-working offices in San Francisco, New York, and London. This role is open to candidates based in North America. EST time zone is preferred for this position. We value deep focus and async collaboration, with intentional moments to connect in person through team off-sites, optional co-working, and occasional travel. What you'll do Own end-to-end implementation plans for enterprise customers: timeline, milestones, dependencies, risk, and stakeholder accountability Run the handoff from Sales at deal close in partnership with Customer Success and Solutions Engineering: validate services scope, timeline commitments, complexity signals, and migration readiness Coordinate workspace architecture, migration, and integration workstreams (SSO/SCIM, Slack, GitHub, Jira sync, custom integrations) across customer IT, Solutions Engineering, and engineering escalations Build the enablement calenda

Developers are shipping more code than ever, accelerated by AI-assisted development and increasingly complex software delivery workflows. As a Product Manager II on the Developer Engagement team, you'll help bring Datadog's insights and automation directly into the tools developers use every day, making software delivery faster, safer, and more efficient. You'll define customer-facing experiences that connect Datadog's observability, CI/CD, testing, security, and AI capabilities with pull requests, code reviews, and developer workflows. This role offers the opportunity to work closely with customers, engineering, design, and go-to-market teams while shaping the future of software delivery for developers. 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: Partner with customers, developers, platform engineering teams, and internal stakeholders to understand software delivery challenges and identify opportunities to improve developer workflows. Own the product strategy and roadmap for developer-facing experiences within pull requests, code reviews, and source code management platforms. Collaborate across Software Delivery products to surface actionable insights from CI/CD Optimization, Test Optimization, Code Coverage, Code Security, Deployment Gates, Bits AI, and future capabilities. Work across source code ecosystems including GitHub, GitLab, Azure DevOps, Bitbucket, and enterprise environments to deliver scalable integrations. Partner with engineering teams to connect Datadog signals with recommendations, AI-assisted workflows, generated fixes, and future automated remediation experiences. Measure product success using customer adoption, engagement, feedback, and business outcomes while partnering with Sales, Product Marketing, Solutions Engineering, Custo

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. NOTE: This position is US - Remote Eligible, but includes monthly in-person working sessions at the San Francisco Airbnb office. The Community You Will Join: Research has been part of Airbnb from the beginning, ever since Paul Graham told the Airbnb founders, "go to your users." As designers, the founders embraced this advice and got on a plane to meet with Airbnb hosts that very weekend. Since those early days, the value of research has been baked into Airbnb’s product culture. The Difference You Will Make: We're building our newest incubation work stream, and we're looking for a Staff UX Researcher who is equally strong in qualitative and quantitative methods. You'll be one of the first researchers on the ground for a 0-to-1 effort, which means the questions aren't defined yet, the roadmap will change, and your research will shape both. You'll know when to run fast to unblock a decision and when to go deep to get it right, while bringing senior stakeholders along the way. A Typical Day: Own end-to-end research for new incubation areas, from framing the questions to landing the recommendations. Utilize appropriate qualitative and quantitative methods to deliver fast, actionable insights. Triangulate across data sources and past learnings to get to the right signals in an ambiguous, fast-moving space. Balance speed and rigor: deliver quick reads when the team needs to move, and deeper studies when a decision warrants it, without sacrificing quality. Partner closely with cross-functional teams including Product, Design, Business Operations, and Data Science to shape strategy from research insights. C

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 Guest Engagement AA sits within Marketing Analytics and serves as the analytical backbone for Airbnb's lifecycle marketing programs — the email, push, and in-app communications that reach hundreds of millions of guests across their entire journey. You'll partner closely with Guest Engagement Marketing, MarTech Data Science, and Strategic Finance to drive measurable booking impact through experimentation and insights. The Difference You Will Make You will be the clear analytics owner of Airbnb's guest lifecycle marketing domain — covering abandon journeys, demand generation, onboarding, upsell, and more. This role is expected to drive significant incremental bookings in 2026 by setting the analytics strategy, designing rigorous experiments, and surfacing proactive insights across 30+ active programs. A Typical Day Own the analytics roadmap for Guest Engagement — define what to measure, what to test, and where the biggest opportunities lie across the full guest lifecycle. Specific projects and prioritization decisions should exist because of your recommendations. Design and analyze experiments at scale across abandon journeys, demand gen ML model rollouts, and placement-level A/B tests. Develop measurement frameworks (holdouts, proxy metrics, annualized impact models) to accurately attribute cumulative program impact. Surface proactive insights that go beyond reporting — user segmentation, funnel analysis, fatigue signals, channel optimization — and translate them into strategic recommendations for Director-level marketing leaders. Build scalable, self-serve reporting (

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 ChatGPT Model Flywheel team unified goal is to transform model advancements into great ChatGPT user experiences through reliable serving, rapid experimentation, safe deployment, and continuous improvement. Team Focus Areas Model Experimentation: Enable rapid, safe model validation for ChatGPT and Codex products through experiment automation and lifecycle management. Model Deployment: Ensure safe, scalable deployment of model capabilities with robust rollout and operational tooling. Automate capacity management and incorporate platform-wide health monitors. Model Measurement: Build comprehensive evaluation and measurement systems for model quality, from user signals to launch scorecards. Improve end-to-end feedback loops for continual model improvement. Key Partnerships Collaborate cross-functionally with teams including Model Measurement DS, Research, Codex, Fleet, Inference, and API. In this role, you will: Elevate and consolidate ChatGPT’s harness, context management, and system prompt frameworks. Drive expansion and improvement of multi-tier model experiences. Support and scale self-serve experiment capabilities and automated guardrails. Lead model rollout automation, capacity management, and health monitoring. Shape end-to-end measurement systems (evals, grader signals, user feedback, etc.). You might thrive in this role if you have: Proven experience leading engineering teams in complex, cross-functional environments. Demonstrated success shipping production systems at scale (ideally for AI or large backend services). Deep understanding of model-driven product development, deployment lifecycle, and measurement tooling. Excellent communication and collaboration skills—experience interfacing directly with engineering, research, and product stakeholders. Prior involvement with large language models, distributed infrastructure, or experimentation platforms is a plus. Why Work With Us Tackle highly impactful technical challenges at the cutting edg

About the Team OpenAI is building AI systems that can help professionals perform complex, high-value work with greater speed, rigor, and creativity. Investment banking is one of the most demanding environments for knowledge work: bankers must synthesize fragmented information, exercise judgment under pressure, and produce precise, defensible models, analyses, and client materials. Our team works across Research, Product, Engineering, and Go-to-Market to make OpenAI's models genuinely useful for these workflows. We translate real professional work into product requirements, evaluations, training signals, and repeatable customer solutions. We care not only whether a model can generate an answer, but whether it can deliver accurate, defensible work that experienced bankers can trust and use. 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. About the Role We are looking for a Subject Matter Expert in Investment Banking to help define what excellent AI-assisted banking work looks like and turn that standard into better models and products. You will bring deep, current knowledge of how investment banking work is actually performed, including company and industry research, financial analysis and modeling, valuation, diligence, transaction execution, and the creation and review of client materials. You will use that expertise to design realistic tasks and evaluations, create and assess high-quality reference work, diagnose model failures, and help our technical teams improve model behavior and product experiences. This is a hands-on individual-contributor role for someone who enjoys both doing the work and explaining what makes it good. You should be comfortable moving between an Excel model, a presentation, a source document, an evaluation rubric, a product prototype, and a conversation with researchers or customers. You will help us distinguish outputs that merely look pl

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 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

Strength in Trust OneTrust’s mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn’t slow teams down—it should accelerate what’s possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI‑Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society. The Challenge As a Senior Staff Software Engineer, you will serve as a technical leader for OneTrust’s AI Governance (AIG) platform, driving the design, scalability, and reliability of systems that enable enterprises to deploy and govern AI and LLM-powered applications responsibly. You will deeply understand how customers build, deploy, and operate AI systems, and translate those needs into secure, compliant, and observable platform capabilities. Your Mission Development Lead the design and development of Java/Python microservices and shared libraries integrating with AI platforms for OneTrust’s AI Governance product. Design, build, and test cloud-native applications deployed on Microsoft Azure using Core Java, REST, and the Spring ecosystem. Lead the architecture and development of reusable AIG reporting and dashboard capabilities that integrate governance data from SQL databases and analytical platforms with runtime observability signals. Design reusable semantic-layer and metric-abstraction capabilities, including dataset contracts, metric defini