Fraud Model Developer in United States

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, Washington D.C., London and Amsterdam. Our Fraud Intelligence team's mission is to turn fraud signals into insight that our EPD teams transform into improvements across Protect, IDV, Signal, and Guaranteed Payments. We believe transaction patterns, device signals, identity linkages, and behavioral data are dramatically underleveraged tools in fraud prevention, and we ground our products in what adversaries are actually doing right now. As the Fraud Intelligence Lead, you will build and run a small, high-leverage team of Fraud Intelligence Analysts (and eventually a Staff Researcher) responsible for live casework across Protect, IDV, and Payments/ACH. You'll operate as a player-coach, hiring and coaching your team while staying close enough to the work to personally pick up casework and SEV response when needed. Responsibilities Team Building & People Leadership Set the casework quality bar: define what rigorous investigation, triage, and reporting look like for the team Coach analysts on investigation technique, pattern synthesis, and translating findings into product/model input Operating Model & Cross-PA Partnership Own coverage allocation across the Protect/IDV and Payments/ACH pods, including flexing assignments as volume shi

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. Our Fraud team's mission is to help companies detect and prevent fraud using Plaid's financial network data. We believe that transaction patterns, device signals, identity linkages, and behavioral data are dramatically underleveraged tools in fraud prevention. Our products — including Protect and Signal — operate at network scale and depend on real-world investigation and research to stay ahead of adaptive adversaries. As a Senior Fraud Researcher, you will sit at the intersection of live fraud investigation, applied data science, and product innovation. You will lead complex investigations, translate findings into detection improvements, and collaborate tightly with Data Science, ML, and Product teams to shape the next generation of Plaid's fraud capabilities. This is not a purely operational role — your research directly drives features, model inputs, and product design. Responsibilities: Live Fraud Investigation & Reconstruction Lead investigations into complex fraud cases across identities, accounts, devices, and transaction surfaces Provide support to day-to-day fraud operations including SEVs and alert triage Reconstruct attacker sequences and hypothesize actor intent and tooling Distill p

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 Data team within Plaid’s Fraud organization. We build the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s network data to help identify and prevent fraud before it happens. Our team owns the end-to-end ML lifecycle, from feature pipelines and model training to production serving and monitoring, ensuring our systems are reliable, scalable, and built to support hundreds of customers and data partners. As a Data Scientist on the Fraud Data team, you will analyze customer and network traffic to understand how Plaid Protect performs across a range of use cases and customer segments. You’ll build dashboards and metrics that provide a clear, shared view of product performance, run backtests to evaluate performance and identify high-impact rules and model strategies, and generate insights that support customer growth and expansion. You’ll also design scalable data models and schemas to enable reliable analysis and reporting, while partnering closely with Product and Engineering to design and analyze experiments for new customer-facing features. Responsibilities: Work at the intersection of product analytics, machine learning, and fraud a

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

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 Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s unique network data to identify and stop fraud before it happens. The team owns the full ML lifecycle—from feature pipelines and model training to production serving and monitoring—building reliable, scalable systems that deliver high-quality fraud detection as we grow to support hundreds of customers. As a Senior Machine Learning Engineer, you will own the development of high-performance feature computation and online inference pipelines that power production machine learning systems at scale. You’ll build robust observability, monitoring, and automated debugging capabilities, while leveraging AI-assisted tools to investigate complex system behavior and maintain high reliability. You’ll partner closely with ML Infrastructure, Data Science, and Product teams to execute critical technical initiatives and deliver scalable, high-impact ML solutions. Responsibilities: Build and scale machine learning systems that power a rapidly growing fraud detection product in a fast-paced environment. Solve complex technical challenges at the intersect

About the Team At OpenAI, our User Operations team safeguards our products and users from legal risk, regulatory non-compliance, fraud, and abuse. The team operates at the intersection of operations, compliance, and user trust, embedded within the broader User Operations organization and collaborating cross-functionally with Legal, Governance Risk & Compliance, Policy and Engineering. We support a global and diverse user base across OpenAI’s suite of product offerings, and developer tools by managing sensitive inbound tickets, regulatory obligations, and escalations. Every user-facing action is grounded in our commitment to legal integrity, ethical practice, and regulatory excellence. About the Role We are seeking an independent, adaptive, and operations-minded Regulatory Operations Analyst to help scale and evolve OpenAI’s global regulatory and compliance operations from San Francisco. This role focuses on complex regulatory operations, including work under the EU Digital Services Act (DSA) and EU AI Act, as well as regulatory inquiries and complaints across the Americas, and Asia-Pacific. You’ll manage sensitive cases independently, exercise sound judgment on escalations, and work closely with Legal Counsel, Governance, Risk and Compliance (GRC), and other cross-functional partners. You’ll also bring a working understanding of privacy and intellectual property matters so you can recognize and escalate related issues when needed. Beyond frontline casework, you’ll help shape the documentation, workflows, tooling, and automation that support safe, scalable and regulatory and legal compliance operations. This role is essential to building scalable, high-integrity operations that protect user rights, meet our obligations under emerging and current regulations. You’ll also contribute to multi-phase transitions and automation efforts that support our long-term operational model. Please note: This role may involve exposure to sensitive or concerning content, including

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. Plaid Protect is a real-time fraud intelligence product built on a unique advantage: Plaid’s network-level visibility across bank accounts, devices, identities, sessions, institutions, applications, and financial behavior. Protect helps customers detect first-party fraud, synthetic identities, account takeovers, and coordinated attacks that are difficult to see from a single application, account, or transaction. Trust Index turns that fraud intelligence into real-time fraud scores and actionable attributes. This team builds the systems that make this intelligence possible: low-latency inference, new data and model integrations, customer-facing APIs and attributes, safe rollouts, and feedback loops. Ti3 expanded Plaid’s fraud graph nearly 10x and, in early testing, detected up to 41% more fraud at the same false-positive rate. Learn more about Ti2 and Ti3 . We are a small, high-agency team working closely with Product, Data Science, and Machine Learning. We value demos over docs, conviction over consensus/alignment, builder schedule over meeting-heavy calendars. We’re scrappy and a talent-dense team that has high agency and high ownership. As a Staff Software Engineer on the Protect Core team, you wi

About the Team At OpenAI, our Trust, Safety & Risk Operations teams safeguard our products, users, and the company from abuse, fraud, scams, regulatory non-compliance, and other emerging risks. We operate at the intersection of operations, compliance, user trust, and safety working closely with Legal, Policy, Engineering, Product, Go-To-Market, and external partners to ensure our platforms are safe, compliant, and trusted by a diverse, global user base. The Global Safety Response Operations team within the org provides 24/7 coverage for user safety, risk, and regulatory escalations across OpenAI’s products, handling the highest-priority cases that require human judgment and rapid response. The team operates as the core escalations management and delivery arm of OpenAI’s safety operations, ensuring that our products remain safe and aligned with our policies while enabling timely, empathetic, and consistent user support. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Please note: This role may involve exposure to sensitive content, including material that is sexual, violent, or otherwise disturbing. About the Role We’re looking for experienced Trust, Safety, and Risk Operations analysts who have subject matter expertise in one or more of the following areas: policy enforcement and content moderation, fraud and scam prevention, developer risk, or privacy and regulatory escalations. You’ll be on the front lines of safety escalation management, helping to triage and resolve urgent and sensitive cases. You’ll work across subject matter areas, systems, and processes to ensure operational excellence, develop process improvements and automations, and surface insights and trends. This is a 24/7 global operation that requires flexibility to work rotating shifts, including nights, weekends, and holidays, as part of an on-call coverage model. We use a hybrid work model of 3 days in the office per week and offer r

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,

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. The Economy ML team sits at the center of this mission. We build ML and AI systems that power personalization, search, pricing, recommendations, and virtual item intelligence across Roblox Economy surfaces, including Avatar Marketplace, Payments, Developer Monetization and Subscriptions. As Roblox continues to invest deeply in AI and ML, this organization also plays a key role in advancing next-generation AI capabilities across the company through close partnership with Discovery, Foundation AI, Engine, Creator and product engineering teams. Our work spans both product impact and foundational ML innovation at Roblox scale. We are looking for a Director of Engineering to lead and scale Economy ML. This leader will define the strategy, organization, and execution model for a fast-growing ML organization spanning recommendation systems, ML infrastructure, search, content intelligence, and Generative AI applications. Why Roblox for ML/AI AI/ML is a top company priority , with strong executive support and long-term investment. Massive real-world scale: Millions of users, creators, and economic interactions every day. Unique technical challenges: Recommendations, pricing, fraud, search, and conte

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. Our Fraud team's mission is to help companies detect and prevent fraud using financial network data. We believe that transaction patterns, device signals, and behavioral data are an underleveraged tool in fraud prevention. The Fraud Consulting Lead is responsible for building and maturing our retro-as-a-service and POC program and driving adoption of our fraud products. The role sits between our data team and the customer (i.e., the role will not build the models, but will need to understand the output well enough to clearly and compellingly present the business case and work with technical stakeholders and customers.) Responsibilities: Own the retro and POC process end-to-end and collaborate with customers and internal stakeholders at Plaid Partner closely with customers to help them understand the ROI of Protect and make recommendations for implementing our fraud products Drive post-retro follow-through to convert retro results into production usage Serve as a feedback loop between customers and product to drive our Protect roadmap Qualifications: 5-10 years of experience in a customer-facing analytical role in fintech, financial services, or a related domain (e.g., software/tech) Experience worki

About the Team The Account & Platform Integrity Operations team protects OpenAI’s ecosystem by ensuring that users, developers, partners, and organizations can access and build on our platform safely and responsibly. The team works across account integrity, fraud prevention, abuse detection, and platform risk to prevent bad actors from exploiting OpenAI’s products and developer surfaces. This role will sit within the Account & Platform Integrity Operations team while partnering closely with teams across the Ecosystem organization to ensure the platform can scale rapidly without compromising trust, quality, or safety. About the Role - Platform Operations Program Manager As OpenAI's developer ecosystem expands, we're building the operational foundation to support the next generation of plugins, MCP apps, agent skills, and integrations. As a Platform Operations Program Manager, you'll partner across Product, Engineering, Policy, Legal, Security, and Developer Experience to design the systems and operating models that enable ecosystem growth while maintaining quality, trust, and an exceptional developer experience. This role requires strong operational judgment, a deep understanding of developer platforms and APIs, empathy for the developer experience, and the ability to translate evolving product, platform, and policy requirements into scalable operational systems. Location: San Francisco, CA (Hybrid - 3 days in office) What You'll Do Own the operational processes that help developers bring apps, plugins, and integrations to market, from submission and review through launch, appeals, and ongoing monitoring. Manage external review partners and policy operations workflows, helping teams apply standards consistently while identifying areas where guidance, process, or quality expectations need to improve. Partner with Product, Engineering, Policy, Legal, Security, Developer Experience, and Go-to-Market teams to turn platform goals and requirements into clear, effec

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

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role We're hiring a hands-on Engineering Manager to build and lead Replit's Anti-Abuse team from the ground up. This is a foundational 0-to-1 role: you'll define the anti-abuse roadmap, hire a small team of engineers and data analysts, and ship the systems that protect Replit's platform, users, and economics from adversarial actors. You'll partner across Support, Legal, Security, Infrastructure, and the Money and Growth teams to make abuse economically unviable while keeping friction low for legitimate users. Replit sits at the frontier of AI-native abuse. Our platform is a target for phishing and scam hosting, cryptomining, LLM token farming, card and coupon fraud, and increasingly, abuse driven by AI agents themselves. The team you build will define how Replit defends against all of it. What You'll Do Build the anti-abuse roadmap from scratch : Define the threat model, prioritize across abuse vectors (phishing/scam hosting, cryptomining, token farming, payment fraud, AI agent exploitation), and translate it into a shipping plan with clear sequencing and tradeoffs. Design progressive verification and identity infrastructure : Build the "ladder of trust" that gates increasing platform capabilities (referrals, additional credits, access to powerful agent features, Missions) behind escalating verification. This includes a humanity/identity layer that's distinct from user accounts, integrations with KYC-grade verification providers, and the policy engine that decides what level of trust unlocks what behavior. This infrastructure is core not just to promo integrity but to how Replit safely expands agent capabilities over time. Ship as a hands-on EM : Stay in the code. Use the latest AI coding tools (including Rep