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, Washington D.C., London and Amsterdam. AI and intelligent systems are driving the fifth paradigm shift, following previous technological revolutions like mainframes, personal computers, the internet, and mobile devices. We believe, in the foreseeable future, AI will revolutionize the FinTech industry - from how consumers understand and manage their finances, to how developers build applications and how all companies operate. The fintech industry landscape will undergo a fundamental reshape. Plaid in the FinTech AI Ecosystem Plaid is uniquely positioned to become the financial data and insights backbone for AI applications and platforms in this evolving ecosystem. We believe consumers should be able to understand and manage their financial life through conversational AI interfaces using natural language. We believe consumers should have peace of mind with a trustworthy consent and authorization manager when agents shop for them. We believe identity verification and financial fraud prevention in AI-powered products should feel seamless and embedded for the end users. The list goes on. The most important AI companies, major fintechs, and customer agent platforms are actively trying to integrate Plaid into AI-powered products and solutions t
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Content Editor in San Francisco
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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, Washington D.C., London and Amsterdam. AI and intelligent systems are driving the fifth paradigm shift, following previous technological revolutions like mainframes, personal computers, the internet, and mobile devices. We believe, in the foreseeable future, AI will revolutionize the FinTech industry - from how consumers understand and manage their finances, to how developers build applications and how all companies operate. The fintech industry landscape will undergo a fundamental reshape. Plaid in the FinTech AI Ecosystem Plaid is uniquely positioned to become the financial data and insights backbone for AI applications and platforms in this evolving ecosystem. We believe consumers should be able to understand and manage their financial life through conversational AI interfaces using natural language. We believe consumers should have peace of mind with a trustworthy consent and authorization manager when agents shop for them. We believe identity verification and financial fraud prevention in AI-powered products should feel seamless and embedded for the end users. The list goes on. The most important AI companies, major fintechs, and customer agent platforms are actively trying to integrate Plaid into AI-powered products and solutions t
What you’ll do Be the generalist EE for the scanner system: integration, bring-up, debugging, and making the electrical side of the device reliable and serviceable. Own ultrasound experimentations that feeds the image reconstruction team Design and execute experiment setups for transducer characterization (element sensitivity, bandwidth, cross-talk mapping, beam profile measurements) and ex vivo / phantom clinical testing. Acquire, process, and analyze RF and baseband signals for data quality assessment and benchmarking. Design simple boards and adapters as needed (monitoring, power/safety, interface/conditioning), and take them from prototype through a stable revision. Prototype quickly, then harden what works: wiring/harnessing, grounding, safety interlocks, and reliable integration across subsystems. Own practical test setups and documentation (fixtures, scripts, procedures) that make experiments repeatable and results comparable over time. What we’re looking for Strong hands-on EE background with experience building, debugging, and iterating on real systems in the lab. Solid understanding of signal processing fundamentals — knows what to measure, how to condition and digitize it, and how to evaluate signal quality in the context of an imaging system (SNR, bandwidth, dynamic range, artifacts). Comfortable spanning system integration + occasional design work (schematics/layout reviews or light PCB design) in a fast-moving environment. Ability to work at the boundary between hardware and algorithms: measure reality, communicate constraints, and help close gaps vs simulation. High agency and practicality: able to set up experiments, get trustworthy data, and unblock others on a lean team. Useful experience Analog/mixed-signal, or high-speed data capture experience; strong instincts for instrumentation and noise/debugging. Ultrasound or acoustic sensor handling: hydrophone calibration and field mapping, transducer impedance characterization, element-level sensitivity
From $232K/yr
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 & Personalization (R&P) team is Airbnb's matching intelligence engine — a talented team of ML engineers, applied researchers, and technical program managers who connect guests to the right listings across every surface and help hosts compete and thrive in our marketplace. We work at the intersection of search ranking, recommendations, personalization, and generative AI, and we're building toward a future where Airbnb feels less like a search engine and more like a knowledgeable travel companion that understands your needs across your entire trip journey. The Difference You Will Make: As Product Manager for Relevance & Personalization, you will help set the strategy and drive execution for some of Airbnb's highest-leverage AI systems. You'll own the roadmap and shape how personalization works across the guest journey, and help define how we close the feedback loop for hosts. You'll partner with engineers, researchers, designers, and cross-functional teams to ship systems that directly drive bookings, guest satisfaction, and host success — at global scale. A Typical Day: Define and drive the roadmap for Airbnb's relevance and personalization platform — from natural language query understanding to multi-turn, context-aware discovery experiences Make prioritization calls that balance multiple competing objectives: guest experience, host success, revenue, fairness, and marketplace health Partner with ML engineers and applied researchers to shape model strategy, evaluation frameworks, and experimentation design Align cross-functional partners — Guest, Host,
About the Team OpenAI for Financial Services is part of OpenAI's Verticals organization, which focuses on accelerating the economy and knowledge work. We build AI products for financial institutions and the professionals who power them, from investment bankers and research analysts to investors and other financial services teams. We combine OpenAI's models, financial data, and enterprise knowledge to help professionals research companies, analyze markets, and produce high-quality work in the tools they use every day. We're a small, entrepreneurial team working closely with customers and partners across research, product, design, engineering, and go-to-market to bring new capabilities from idea to production. About the Role We're looking for full-stack engineers to build new, AI-native products on top of ChatGPT Work and Codex. This is zero-to-one work: you'll help define how financial professionals research, analyze, and make decisions alongside AI. You'll own the experience across the stack, work directly with customers to understand their workflows, and collaborate across OpenAI to turn new model capabilities into products that professionals can trust. Your work will shape how some of the world's largest financial institutions adopt AI and how financial knowledge work gets done. In this role, you will: Build a new financial services app within ChatGPT Work and Codex, creating intuitive AI-native experiences for company research, financial analysis, document review, and professional work products. Develop new product experiences around enterprise memory that learn from an organization's knowledge, workflows, and context, and adapt to how its teams work. Develop the APIs, services, and integrations required to connect user experiences with financial data providers, enterprise systems, and OpenAI's models. Work closely with product and design to turn ambiguous customer problems into polished, useful, and reliable products. Work directly with financial institutions to
About the Team The Growth team drives user and revenue growth across ChatGPT’s consumer and business segments as well as other OpenAI products worldwide. We operate across the full funnel - from awareness and acquisition through activation, retention, and expansion - using a combination of global performance marketing, AI-powered workflows, in-product optimization, insights, experimentation, and creative ops engineering. About the Role We are hiring a Lifecycle Lead to build the company-wide owned-channel capability that helps teams reach users with relevant, timely, and trustworthy experiences. This senior, hands-on leader will set the lifecycle strategy, partner with Engineering to build the orchestration and deployment platform, and establish the operating model that allows teams across the company to launch and improve evergreen programs safely at scale. You will sit at the intersection of platform, product, and campaign strategy. You will partner with Engineering, Product, Data Science, and Analytics on the underlying systems, and with Product Marketing Managers and other client teams to design journeys that help new, active, and returning users reach value and build durable habits. In this role, you will: Partner with product to set the company-wide vision, roadmap, and operating model for lifecycle and owned-channel engagement. Partner with Engineering, Product, Data Science, and Analytics to shape the tooling and infrastructure for identity, audiences, eligibility, consent, triggers, orchestration, decisioning, frequency, experimentation, localization, quality assurance, and observability. Define scalable deployment workflows—including self-service and centrally supported paths, intake, templates, approvals, governance, service levels, and incident response—so teams across the company can launch safely and efficiently. Partner with Product Marketing Managers and other client teams to translate audience, product, and business goals into evergreen journey stra
About the Team OpenAI’s Business Marketing team helps organizations understand, adopt, and create value with AI. Integrated Marketing connects our brand, products, customers, developer communities, go-to-market teams, and commercial priorities into coherent market moments. We are building an AI-native marketing team that moves quickly, uses intelligence to work differently, and measures success by whether business audiences become aware of OpenAI, consider our products, and ultimately choose us. About the Role We’re hiring an integrated marketer to shape how businesses understand, experience, and choose OpenAI. You’ll connect our brand, products, and customer stories into campaigns that demonstrate how AI is transforming organizations and establish OpenAI as a preferred partner for businesses adopting AI. You’ll build integrated campaigns for BDMs, and grow customer relationships through storytelling as a critical source of proof of enterprise transformation.. This role is part of the Integrated Marketing team within OpenAI’s Business Marketing organization. While your specialty is brand and customer, you’ll flex across business campaigns, product launches, and other priority market moments. In this role, you will: Lead integrated brand marketing strategies and campaigns that increase awareness, consideration, and preference among enterprise buyers and business decision makers. Synthesize audience research, cultural/competitive context, product truth, customer proof, and business priorities into positioning and creative briefs that can travel across paid, owned, earned, social, field, and sales channels. Connect brand, creative, customer marketing, communications, media, growth, demand generation, and field activation into one coherent business audience journey. Use AI to uncover insights, experiment with new storytelling formats, and accelerate high-quality execution. Be directly accountable for increasing unaided awareness, consideration, purchase preference, and
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 The HR Business Partner (HRBP) team at OpenAI helps shape how our organization operates and performs. We work alongside senior leaders and their teams to design effective organizations, strengthen leadership capabilities, and help people do their best work. Our expertise spans leadership coaching, organizational design, talent strategy, employee relations, and change management. Our work is grounded in a deep understanding of OpenAI’s Contributions & Impact (C&I) culture and the needs of teams working at the frontier of AI and hardware. We operate with urgency, empathy, and sound judgment. We value sincerity over polish, collaboration over ego, and a relentless focus on meaningful impact. About the Role We’re looking for an experienced HR Business Partner to support OpenAI’s Consumer Device's team. This is an opportunity to partner closely with leaders and teams doing highly ambitious, multidisciplinary work. You’ll serve as a trusted advisor as the organization builds, collaborates, and evolves—helping create the conditions for people and teams to perform at their best. The role combines strategic advising with hands-on partnership. You’ll help leaders think through organizational questions, coach managers through complex situations, strengthen people practices, and make thoughtful trade-offs that balance the needs of our people, teams, and mission. This is an individual contributor role. Come build with us. Your Key Responsibilities Shape high-performing, resilient teams: Partner with leaders on organizational design, talent planning, and ways of working that support strong performance and sustainable teams. Advise with context and judgment: Develop a deep understanding of the organization and provide thoughtful guidance on people, leadership, and organizational matters. Collaborate across OpenAI: Work closely with fellow HRBPs, People centers of excellence, and cross-functional partners to create a cohesive employee experience rooted in hum
About the Team The GTM Data Science team partners with Go-to-Market, Technical Success, Product, Engineering, RevOps, and Strategic Finance to build the shared intelligence layer for OpenAI's B2B business. The team turns product usage, customer behavior, revenue, field activity, and customer feedback into rigorous insight products that help leaders and field teams understand where customers are succeeding, where adoption is blocked, and what actions will accelerate durable growth. We are building systems that make customer intelligence proactive: surfacing risk, expansion potential, product gaps, and repeatable playbooks before they show up as escalations or missed opportunities. About the Role As the Applied Data Science & Insights Lead for GTM Intelligence Solutions and Technical Success, you will be a hands-on technical leader responsible for shaping how OpenAI measures, understands, and improves customer adoption across our B2B products. You will build AI/ML-powered intelligence products that connect account health, product usage, customer lifecycle, support tier, qualitative sentiment, commercial context, and field actions into a practical operating system for GTM and Technical Success. This role will build the data science foundation for Technical Success: defining the metrics, models, operating insights, and decision systems that help the team scale customer adoption and expansion with rigor. You will also be expected to build and lead a small mighty team over time: setting direction, hiring and developing talent, creating operating cadences, and holding a high bar for technical rigor and business impact. You will lead the development of models, metrics, and decision systems that recommend what GTM and Technical Success teams should do next, explain why, and measure whether those interventions worked. Your work will help customers move from pilots to production, deepen usage across products, identify high-value use cases, reduce churn risk, and create a f
The ChatGPT Finances team builds experiences that help people connect their financial accounts, understand their financial picture, and ask useful questions about their finances through ChatGPT. Our work spans account connectivity, data ingestion, dashboards, personalized insights, and conversational experiences. We collaborate across product, design, research, infrastructure, security, and data integrations to make complex financial information understandable and actionable. This is an early and ambitious product area with a substantial roadmap. We are looking for engineers who want to shape both the first user experiences and the durable systems required to earn and keep users’ trust. About the role We’re looking for full-stack product engineers to build and scale ChatGPT Finances. You will own features across the stack—from polished frontend experiences to the APIs, services, and data models that power them. This role is well suited to engineers who combine strong product judgment with broad technical depth. You should care about how quickly users can understand their financial lives, how reliably data moves through the system, and how AI can answer financial questions in a grounded, transparent, and useful way. You will work closely with product, design, research, infrastructure, security, and data integration teams to take ideas from early prototypes to reliable production experiences. In this role, you will Own full-stack product features from user experience and frontend implementation through backend services, data models, deployment, and observability. Build polished, accessible, and performant interfaces for account connection, dashboards, insights, and conversational workflows. Design APIs and backend systems that safely ingest, normalize, and serve financial data. Build resilient integrations that handle synchronization, data freshness, partial failures, permissions, and user consent. Bring new AI capabilities into production while prioritizing grounding
About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Connectors, you will teach models how to interface with the top professional software using code. You will help train agents to use code, APIs, tools, and structured integrations to operate across applications like Slack, Google Workspace, GitHub, Notion, Linear, Salesforce, and other core systems of work. You will help enable models to take useful actions across a user’s digital context: finding information, updating systems, coordinating work, generating artifacts, and completing multi-step workflows through the tools teams already use. You will train models to be supercharged by the world’s most important productivity and enterprise software, turning connected tools into a powerful action surface for our agents. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people.
About the Team OpenAI's Compensation team plays a crucial role in rewarding and retaining world-class talent who will ensure that artificial general intelligence benefits all of humanity. By crafting and implementing innovative compensation strategies, we ensure our compensation offerings are competitive, equitable, and aligned with OpenAI's mission to scale intelligently and ethically. About the Role We are expanding our Compensation team and seeking a Compensation Business Partner to help build the compensation pillar for our go-to-market organization. This is a hands-on individual-contributor role for someone who brings deep GTM compensation expertise and enjoys turning evolving business needs into practical, scalable programs. As a member of the total rewards team, you will partner closely with GTM leaders, HR Business Partners, Recruiting, Finance, and other cross-functional teams. You will spearhead compensation work across benchmarking, offer review, program design, and job architecture, with particular focus on the needs of a rapidly growing commercial organization. The shape of the work will evolve as the business grows. At times, you may independently lead key initiatives from strategy through execution. At other times, you will work alongside additional compensation partners and cross-functional resources. Success in this role requires comfort operating with ambiguity, strong judgment, and a willingness to stay close to the details while building for scale. This is an individual contributor role, designed for a subject-matter expert and hands-on builder. In this role, you will: Build and evolve compensation programs that support OpenAI’s growing GTM organization. Serve as a trusted compensation advisor to GTM leaders, HR Business Partners, Recruiting, and Finance. Lead compensation analysis and approval for offers, balancing market context, internal consistency, and OpenAI’s compensation philosophy. Own benchmarking and market analysis for GTM roles, tran
About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team builds the data, environments, graders, training methods, and feedback loops that shape what OpenAI’s next agents can do and what they are like to work with, then carries those improvements through major training runs and into products used by people every day. About the Role As a member of the Agent Post-training Personality team, you will help make OpenAI’s agents exceptional collaborators. You will study what makes an agent thoughtful, clear, perceptive, appropriately proactive, and genuinely easy to work with, then translate those insights into evals, training data, reward signals, and model improvements. We use “personality” to mean much more than writing style or general likability. It includes whether an agent understands what the user is trying to accomplish, communicates with good judgment, adapts to context, asks useful questions, handles disagreement honestly and takes initiative at the right moments. The goal is to create a strong, tasteful default that can adapt to different people and situations. This work combines behavioral research, product thinking, research and communication taste. You will collaborate with product teams, human experts, and researchers across post-training and pretraining to ensure that improvements survive the full trai
About the Team OpenAI’s mission is to build safe artificial general intelligence (AGI) that benefits all of humanity. Achieving this requires bringing the world’s most exceptional talent under one roof to push the boundaries of what’s possible. Our Research Recruiting team plays a critical role in this effort. We are an embedded part of the research organization—working side by side with our research staff to deeply understand evolving priorities, build trust, and strategically shape the future of OpenAI’s talent. About the Role We are looking for a highly strategic recruiter to work closely with the Head of Research Recruiting on a small set of unusually important, high-touch searches and candidate relationships. This role will focus on exceptional talent who does not move through a standard recruiting process: highly visible researchers, technical leaders, operators, and other special-interest candidates where timing, discretion, market intelligence, and tailored engagement matter as much as process execution. This is not a conventional req-based recruiting role. You will help identify where the market is moving, develop intelligence on top talent and competitor activity, translate that intelligence into action, and orchestrate bespoke recruiting strategies for candidates who require a more nuanced path into OpenAI. You should be able to translate these signals and states into clear, actionable advice for leaders and then make it happen. In this role, you will: Partner directly with the Head of Research Recruiting and research leadership team to define priority talent targets and shape bespoke engagement strategies. Build and maintain deep market intelligence across frontier AI, research, engineering, and adjacent talent ecosystems, including competitor movement, candidate motivations, and relationship context. Proactively identify, map, and cultivate exceptional high-profile talent before there is a formal or standard hiring process attached. Translate weak signa
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