Senior Fraud Model Developer Jobs

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. 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

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 Netlify runs on usage. Developers buy credits, teams consume compute and bandwidth, and enterprises commit to spend. The Accounts and Billing area owns how all of that works: the accounts foundation every customer signs into, the billing platform that meters and charges them, and the pricing and packaging model that sets what they pay. It sits at the center of how Netlify grows, and it touches Finance, Growth, UX, Sales, and the executive team. As a Staff Product Manager, you’ll help define and evolve Netlify’s monetization model, bringing a strong point of view while partnering across the company to make high-impact decisions, and you will build hands-on next to engineering, Finance, and design rather than run a team from above. You’ll collaborate closely with senior leaders, including the CEO and CFO, as we continue to evolve Netlify’s pricing and packaging strategy. What You'll Do Lead the strategy and evolution of pricing, packaging, and monetization, including plans and tiers, the credit and usage model, seat-versus-consumption economics, on-demand and overage rates, enterprise commitments and discounting, storage pricing, regional pricing, and annual plans. Ship billing as a product: metering accuracy, invoicing, payments, refunds, and customer-facing usage visibility, including the billing and usage interfaces enterprises are asking for. Steward the accounts foundation: sign-up and authentication, identity, orgs and teams and seats, roles and permissions, account security, and fraud and abuse at the top of the funnel. Build and lead the pricing and packaging experimentation program, using data, customer insight, and sound judgment to guide decisions: product analytics, conversion and activation, and credit-consumption telemetry. Partner with Finance to develop pricing approaches that balance customer value, business goals, and long-term sustainability. Partner with engineering and cross-functional stakeholders to set priorities, evaluate tradeo

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

About Paytm: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. About the Team: The Credit Risk Product Team is at the core of our lending operations, ensuring that our risk assessment models are efficient, scalable, and compliant with regulatory frameworks. The team collaborates closely with data scientists, engineers, and business stakeholders to develop and enhance credit risk models, decisioning frameworks, and risk mitigation strategies. By leveraging advanced analytics and machine learning, the team continuously refines underwriting processes to optimize loan performance and reduce defaults. About the Role: We are looking for a rockstar Senior Product Manager – Lending Risk to lead the Merchant Lending Risk charter at Paytm. You will own the risk product strategy that powers unsecured merchant loans, balancing aggressive growth with rock-solid credit quality and regulatory integrity, while partnering closely with Risk, Data Science, Engineering & Business. Key Responsibilities: * Define and drive the product roadmap for merchant lending risk. * Build and scale rule engines (BRE), decision engines, and model orchestration layers. * Implement audit-ready decision logs and explainability layers. * Build robust policy versioning and experimentation infrastructure. * Lead a team of credit risk analysts owning underwriting, risk, fraud, and monitoring. Requirements: * 5+ years of product management experience in the consumer or fintech industry. * Strong experience in unsecured merchant or SME lending preferred * Strong analytical and structured thinking ability. Why join us •A collaborative output driven program that brings cohesiveness across businesses through tech

About the Team At OpenAI, our User Safety & Risk Operations (USRO) team helps protect our products and users from abuse, fraud, safety risks, and other forms of misuse. We operate at the front line of real-world safety and risk management, translating user and operational signals into timely decisions, effective interventions, and improvements to our systems. This role sits on a new team within USRO focused on building operational capacity for new, ambiguous, or fast-moving areas of work. The team helps define what needs to be built, creates the operating model to support it, and works with partner teams to make the work scalable and durable over time. As a Strategic Operations Lead, you will focus on large, cross-functional initiatives that require clear thinking, technical fluency, strong execution, and the ability to bring structure to undefined problems. About the Role We are seeking a Strategic Operations Lead to drive new and existing strategic operating builds across User Safety & Risk Operations. This is a senior IC role for someone who can turn broad, undefined priorities into clear operating models, launch plans, requirements, stakeholder alignment, documentation, reporting, and execution rhythms. This role will often support initiatives where OpenAI is developing new products or partnerships and the operating model is still being defined. These programs have a direct user safety and risk nexus because new deployment models can change what signals OpenAI can see, who owns response decisions, and how user-impacting risks are detected, escalated, and resolved. You will clarify what OpenAI owns, what partner teams own, what signals we can reliably monitor, how issues should be escalated, and how the workflow should evolve from launch support into a durable operating model. The right person is highly strategic and deeply practical. They can move from executive-level framing to detailed workflow design, stakeholder management, SOPs, launch readiness, ri

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: Everyone at Airbnb thinks about trust, but our team obsesses over it daily. At the core of trust is safety, and thus we spend a significant amount of our time and energy keeping the community safe. The Trust team is responsible for developing the technology that helps protect our community and platform from fraud while also ensuring our hosts, guests, homes, and experiences meet our high standards. We constantly work to fight against online fraud (such as monetary loss, compromised accounts, spam and scam in messages, fake inventory, etc.) as well as offline fraud (theft, property damage, personal safety, etc.). We also work on onboarding and screening of users, and think about complex topics like identity and reputation to ensure that every interaction with Airbnb helps build trust in us and our community. You'll work side-by-side with talented product managers, data scientists, software engineers, fraud intelligence, and operations teams. Together, you'll design and build ML solutions that have direct, meaningful impact on user trust, business success, and the global Airbnb community. The Difference You Will Make: As a Senior Machine Learning Engineer on the Trust team, you will actively contribute code and ideas that shape the ML systems protecting millions of Airbnb users. You'll own and deliver ML projects end-to-end — from designing and training models to productionizing and operating them at scale, while collaborating closely with cross-functional partners. You'll tackle real-world challenges such as account takeover, fake accounts, payment fraud, and bot detection. Your work

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Trust and confidence is fundamental to the Lyft marketplace, and the Pay, Integrity & Identity (PII) Analytics team is charged with providing and ensuring that trust and safety to all customers. The PII Analytics team is one of the most critical teams that helps protect Lyft and enables the company to grow in a sustainable way. The team is fast-paced, high-energy, and meticulous in diagnosing emerging fraud patterns and preventing fraud loss before it can happen. We drill holes in all the products we launch and obsess over how to make our business impervious to fraud vectors. The team conducts a rigorous analysis of complex data sets and sets up multiple layers of business rules, models, and other processes to prevent potential fraud. We are a highly cross-functional team and regularly engage in discussion and reviews with stakeholders to prioritize plans for reducing fraud impact and introducing safety features. We’re looking for a rock-star to join a fast-paced environment to contribute to Fraud-related analysis and operations. This individual is responsible for investigating and developing solutions to prevent and mitigate third party fraud. This person will proactively identify fraud patterns and sources to minimize the company’s exposure to financial and reputational risk. The Senior Analyst will take ownership over multiple discrete fraud segments to develop and execute a strategy which addresses fraud in the earliest stages of detection. The Senior Analyst will define fraud prevention measures that are mindful of the impact on good user experience while inhibiting fraud actors’ ability to reach our platform. This person is quantitatively driven, detail-focused, and operations-savvy while ensuring the best possible customer experience. This individual possesses a high level of subject matte

At Trustpilot, we're on an incredible journey. We're a profitable, high-growth FTSE-250 company with a big vision: to become the universal symbol of trust. We run the world's largest open customer review platform, and while we've come a long way, there's still so much exciting work to do. Come join us at the heart of trust! We are growing our engineering team at Trustpilot and are looking to welcome a Software Engineer I into the Trust Tech department! You will join a cross-functional team with full ownership of our products and codebase, where you will take part in every step of the development process, from ideation to maintenance. This is a place where you can grow as an individual, learn from senior mentors, and have a real influence on the direction of our projects. About the team: You will be joining a brand new team being built within the Trust Tech department, focusing specifically on businesses. The team is responsible for building and maintaining automated systems that enforce Trustpilot’s terms of use for businesses. This includes developing systems for automatic detection, enforcement of misuse, and internal investigation tools. This work is vital to maintaining Trust and Transparency on the platform. To achieve this, we collaborate closely with Data Scientists, Data Ops, and ML Ops to build sophisticated automated architectures that integrate detection models and robustly scale our misuse enforcement. What you’ll be doing: Work in a cross-functional “full ownership” team alongside Product, Design, and Data Science. Implement and release new features with a focus on backend stability and scalability. Help build solutions to handle high-volume data processing for fraud detection. Maintain and improve the internal tooling frontends (React) used for investigations. Troubleshoot existing software, squash bugs, and learn how to optimize database performance. Participate in technical discussions and learn best practices for Infrastructure as Code. Collab

At Trustpilot, we're on an incredible journey. We're a profitable, high-growth FTSE-250 company with a big vision: to become the universal symbol of trust. We run the world's largest open customer review platform, and while we've come a long way, there's still so much exciting work to do. Come join us at the heart of trust! We are growing our engineering team at Trustpilot and are looking to welcome a Software Engineer I into the Trust Tech department! You will join a cross-functional team with full ownership of our products and codebase, where you will take part in every step of the development process, from ideation to maintenance. This is a place where you can grow as an individual, learn from senior mentors, and have a real influence on the direction of our projects. About the team: You will be joining a brand new team being built within the Trust Tech department, focusing specifically on businesses. The team is responsible for building and maintaining automated systems that enforce Trustpilot’s terms of use for businesses. This includes developing systems for automatic detection, enforcement of misuse, and internal investigation tools. This work is vital to maintaining Trust and Transparency on the platform. To achieve this, we collaborate closely with Data Scientists, Data Ops, and ML Ops to build sophisticated automated architectures that integrate detection models and robustly scale our misuse enforcement. What you’ll be doing: Work in a cross-functional “full ownership” team alongside Product, Design, and Data Science. Implement and release new features with a focus on backend stability and scalability. Help build solutions to handle high-volume data processing for fraud detection. Maintain and improve the internal tooling frontends (React) used for investigations. Troubleshoot existing software, squash bugs, and learn how to optimize database performance. Participate in technical discussions and learn best practices for Infrastructure a

At Trustpilot, we're on an incredible journey. We're a profitable, high-growth FTSE-250 company with a big vision: to become the universal symbol of trust. We run the world's largest open customer review platform, and while we've come a long way, there's still so much exciting work to do. Come join us at the heart of trust! We are growing our engineering team at Trustpilot and are looking to welcome a Software Engineer I into the Trust Tech department! You will join a cross-functional team with full ownership of our products and codebase, where you will take part in every step of the development process, from ideation to maintenance. This is a place where you can grow as an individual, learn from senior mentors, and have a real influence on the direction of our projects. About the team: You will be joining a brand new team being built within the Trust Tech department, focusing specifically on businesses. The team is responsible for building and maintaining automated systems that enforce Trustpilot’s terms of use for businesses. This includes developing systems for automatic detection, enforcement of misuse, and internal investigation tools. This work is vital to maintaining Trust and Transparency on the platform. To achieve this, we collaborate closely with Data Scientists, Data Ops, and ML Ops to build sophisticated automated architectures that integrate detection models and robustly scale our misuse enforcement. What you’ll be doing: Work in a cross-functional “full ownership” team alongside Product, Design, and Data Science. Implement and release new features with a focus on backend stability and scalability. Help build solutions to handle high-volume data processing for fraud detection. Maintain and improve the internal tooling frontends (React) used for investigations. Troubleshoot existing software, squash bugs, and learn how to optimize database performance. Participate in technical discussions and learn best practices for Infrastructure a

At Trustpilot, we're on an incredible journey. We're a profitable, high-growth FTSE-250 company with a big vision: to become the universal symbol of trust. We run the world's largest open customer review platform, and while we've come a long way, there's still so much exciting work to do. Come join us at the heart of trust! We are growing our engineering team at Trustpilot and are looking to welcome a Software Engineer I into the Trust Tech department! You will join a cross-functional team with full ownership of our products and codebase, where you will take part in every step of the development process, from ideation to maintenance. This is a place where you can grow as an individual, learn from senior mentors, and have a real influence on the direction of our projects. About the team: You will be joining a brand new team being built within the Trust Tech department, focusing specifically on businesses. The team is responsible for building and maintaining automated systems that enforce Trustpilot’s terms of use for businesses. This includes developing systems for automatic detection, enforcement of misuse, and internal investigation tools. This work is vital to maintaining Trust and Transparency on the platform. To achieve this, we collaborate closely with Data Scientists, Data Ops, and ML Ops to build sophisticated automated architectures that integrate detection models and robustly scale our misuse enforcement. What you’ll be doing: Work in a cross-functional “full ownership” team alongside Product, Design, and Data Science. Implement and release new features with a focus on backend stability and scalability. Help build solutions to handle high-volume data processing for fraud detection. Maintain and improve the internal tooling frontends (React) used for investigations. Troubleshoot existing software, squash bugs, and learn how to optimize database performance. Participate in technical discussions and learn best practices for Infrastructure a