Plaid

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.

The Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s newest fraud detection products, leveraging the breadth of Plaid’s network data to stop fraud before it occurs. We manage the full lifecycle of these systems—from feature pipeline development and model training to deployment, serving, and monitoring—ensuring our solutions scale reliably as we grow to support hundreds of customers.

As a Data Scientist on Plaid’s Fraud Data team, you will analyze customer and network traffic to understand how Protect performs across different segments and use cases. You’ll build dashboards and performance metrics that create a clear, shared view of product health for both the team and our go-to-market partners. You will run backtests on customer traffic to evaluate model and rule performance, uncover high-value opportunities, and generate insights that support sales motions and customer expansion. You’ll also design the underlying data models and schemas that enable efficient, reliable analysis and reporting. In close partnership with Product and Engineering, you will help design and evaluate experiments that shape new customer-facing features and inform the future of our fraud products.

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.

The Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s newest fraud detection products, leveraging the breadth of Plaid’s network data to stop fraud before it occurs. We manage the full lifecycle of these systems—from feature pipeline development and model training to deployment, serving, and monitoring—ensuring our solutions scale reliably as we grow to support hundreds of customers.

As a Data Scientist on Plaid’s Fraud Data team, you will analyze customer and network traffic to understand how Protect performs across different segments and use cases. You’ll build dashboards and performance metrics that create a clear, shared view of product health for both the team and our go-to-market partners. You will run backtests on customer traffic to evaluate model and rule performance, uncover high-value opportunities, and generate insights that support sales motions and customer expansion. You’ll also design the underlying data models and schemas that enable efficient, reliable analysis and reporting. In close partnership with Product and Engineering, you will help design and evaluate experiments that shape new customer-facing features and inform the future of our fraud products.

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.

The Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s newest fraud detection products, leveraging the breadth of Plaid’s network data to stop fraud before it occurs. We manage the full lifecycle of these systems—from feature pipeline development and model training to deployment, serving, and monitoring—ensuring our solutions scale reliably as we grow to support hundreds of customers.

As a Data Scientist on Plaid’s Fraud Data team, you will analyze customer and network traffic to understand how Protect performs across different segments and use cases. You’ll build dashboards and performance metrics that create a clear, shared view of product health for both the team and our go-to-market partners. You will run backtests on customer traffic to evaluate model and rule performance, uncover high-value opportunities, and generate insights that support sales motions and customer expansion. You’ll also design the underlying data models and schemas that enable efficient, reliable analysis and reporting. In close partnership with Product and Engineering, you will help design and evaluate experiments that shape new customer-facing features and inform the future of our fraud products.

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 they build.

Plaid’s AI-powered Experiences for Customers

The explosive growth in model intelligence and increasing relevance for enterprise tasks offer a unique opportunity for Plaid to rethink from the ground up how we operate and interact with our customers for the most optimal experience.

Our early experiments in building AI agents for customer experience are paying off with huge business value. For example, our homegrown AI-powered customer support agents resolve a significant proportion of customer questions and issues within seconds, which would otherwise have required humans hours to work on.

This is just the beginning and there is so much more we could do.

The AI Applications Team

You will have the opportunity to join as one of the founding members of this newly formed team that is dedicated to consolidating and rapidly scaling our successful bets so far, and grow with the team in our quest to accelerate Plaid’s transformation into an AI-first company.

In this role you will lead projects that enable and scale our business with our largest AI customers and partners, starting with personal finance use cases and expanding into many others; examples include:

• Develop and evolve the preferred integration pattern for Plaid with AI providers - from API adaptations to building the official Plaid MCP Servers, and beyond
• Redefine how Plaid’s consumer link experience embed into conversational interfaces in the most seamless way
• Architect the trust layer for the future of agentic commerce that will become the industry standard

Additionally you will be expected to scale and extend our existing successful bets on AI-powered customer experience; examples include:

• Make the next step-function improvement in our homegrown customer support agent - land our multi-turn and multi-agent system that powers a truly delightful experience for our customers; define how to scalably run offline evaluation for complex multi-turn open-ended tasks; research and prototype how Human-In-The-Loop - Reinforcement Learning (RLHF) can power an insights flywheel; pioneer the architecture for customer-specific long-term memory, etc.
• Extend our agentic system to support other critical parts of the customer journey, starting with areas with the highest ROI - top-of-funnel product recommendation, customer onboarding and risk diligence, customer activation and assistance for faster productionization, as well as upselling and cross-selling of Plaid products

You will have a front row seat to all the latest industry developments. Over time, with the skills and experience you develop and hone on this team, you can become an influential voice in defining where AI <> Fintech will be heading longer term.

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. #LI-Remote

Plaid’s Machine Learning team is building models that improve how millions of users understand and grow their financial lives. We're looking for machine learning engineers with experience applying state-of-the-art machine learning and modeling techniques -- including natural language processing, anomaly detection, optimization, and time series forecasting -- toward different product areas. We value not only technical know-how, but also creativity, user empathy, and teamwork.

You’ll be a machine learning engineer as a part of the core ML payments team, contributing to diverse, high-impact machine learning challenges. Specifically, you will focus on designing, building and deploying scalable ML solutions and systems. You will lead the efforts to experiment with new modeling approaches and strategies, as well as collaborating closely with a skilled team of engineers on ingesting signals and productionizing these models. If you're interested in building the state of art AI/ML solutions to unblock financial freedom for everyone, let's chat!

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.

Making data driven decisions is key to Plaid's culture. To support that, we need to scale our data systems while maintaining correct and complete data. We provide tooling and guidance to teams across engineering, product, and business and help them explore our data quickly and safely to get the data insights they need, which ultimately helps Plaid serve our customers more effectively. We build the data and machine learning infrastructure to enable Plaid engineers to prototype and iterate on products and features built on top of consumer-permissioned financial data.

Engineers on Data Infrastructure are domain experts in Data Warehouse, Data Lakehouse, Spark, Workflow Orchestration, and Streaming technologies. We scale our existing data pipelines in a performant and cost efficient way while creating the necessary abstractions to make developing on top of this platform extremely simple for other engineers at Plaid.

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.

The Data team within Plaid’s Fraud organization builds the machine learning systems behind Plaid’s next-generation fraud detection products. Leveraging Plaid’s unique network data, the team develops end-to-end solutions to identify and prevent fraud before it happens. This includes ownership across the full ML lifecycle, from large-scale data processing and model experimentation to feature pipelines, model serving, and ongoing performance monitoring.

As a Senior Machine Learning Engineer (Research Scientist) you will lead applied research to develop next-generation fraud detection models across complex data modalities, including relational graphs, sequential events, images, and video. You will design and run rigorous experiments and build evaluation methodologies that reflect real-world fraud dynamics, prototype state-of-the-art architectures such as Graph Neural Networks and Transformer-based foundation models, and partner closely with Machine Learning Engineers to translate successful research into production systems. The role also involves communicating and publishing results internally and externally, helping raise the technical bar for fraud machine learning at Plaid.

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. #LI-Remote

Plaid’s Machine Learning team is building models that improve how millions of users understand and grow their financial lives. We're looking for machine learning engineers with experience applying state-of-the-art machine learning and modeling techniques -- including natural language processing, anomaly detection, optimization, and time series forecasting -- toward different product areas. We value not only technical know-how, but also creativity, user empathy, and teamwork.

You’ll be a machine learning engineer as a part of the core ML payments team, contributing to diverse, high-impact machine learning challenges. Specifically, you will focus on designing, building and deploying scalable ML solutions and systems. You will lead the efforts to experiment with new modeling approaches and strategies, as well as collaborating closely with a skilled team of engineers on ingesting signals and productionizing these models. If you're interested in building the state of art AI/ML solutions to unblock financial freedom for everyone, let's chat!

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.

The Data team within Plaid’s Fraud organization builds the machine learning systems behind Plaid’s next-generation fraud detection products. Leveraging Plaid’s unique network data, the team develops end-to-end solutions to identify and prevent fraud before it happens. This includes ownership across the full ML lifecycle, from large-scale data processing and model experimentation to feature pipelines, model serving, and ongoing performance monitoring.

As a Senior Machine Learning Engineer (Research Scientist) you will lead applied research to develop next-generation fraud detection models across complex data modalities, including relational graphs, sequential events, images, and video. You will design and run rigorous experiments and build evaluation methodologies that reflect real-world fraud dynamics, prototype state-of-the-art architectures such as Graph Neural Networks and Transformer-based foundation models, and partner closely with Machine Learning Engineers to translate successful research into production systems. The role also involves communicating and publishing results internally and externally, helping raise the technical bar for fraud machine learning at Plaid.

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.

Making data driven decisions is key to Plaid's culture. To support that, we need to scale our data systems while maintaining correct and complete data. We provide tooling and guidance to teams across engineering, product, and business and help them explore our data quickly and safely to get the data insights they need, which ultimately helps Plaid serve our customers more effectively. We build the data and machine learning infrastructure to enable Plaid engineers to prototype and iterate on products and features built on top of consumer-permissioned financial data.

Engineers on Data Infrastructure are domain experts in Data Warehouse, Data Lakehouse, Spark, Workflow Orchestration, and Streaming technologies. We scale our existing data pipelines in a performant and cost efficient way while creating the necessary abstractions to make developing on top of this platform extremely simple for other engineers at Plaid.

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.

The Data team within Plaid’s Fraud organization builds the machine learning systems behind Plaid’s next-generation fraud detection products. Leveraging Plaid’s unique network data, the team develops end-to-end solutions to identify and prevent fraud before it happens. This includes ownership across the full ML lifecycle, from large-scale data processing and model experimentation to feature pipelines, model serving, and ongoing performance monitoring.

As a Senior Machine Learning Engineer (Research Scientist) you will lead applied research to develop next-generation fraud detection models across complex data modalities, including relational graphs, sequential events, images, and video. You will design and run rigorous experiments and build evaluation methodologies that reflect real-world fraud dynamics, prototype state-of-the-art architectures such as Graph Neural Networks and Transformer-based foundation models, and partner closely with Machine Learning Engineers to translate successful research into production systems. The role also involves communicating and publishing results internally and externally, helping raise the technical bar for fraud machine learning at Plaid.

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. #LI-Remote

Plaid’s Machine Learning team is building models that improve how millions of users understand and grow their financial lives. We're looking for machine learning engineers with experience applying state-of-the-art machine learning and modeling techniques -- including natural language processing, anomaly detection, optimization, and time series forecasting -- toward different product areas. We value not only technical know-how, but also creativity, user empathy, and teamwork.

You’ll be a machine learning engineer as a part of the core ML payments team, contributing to diverse, high-impact machine learning challenges. Specifically, you will focus on designing, building and deploying scalable ML solutions and systems. You will lead the efforts to experiment with new modeling approaches and strategies, as well as collaborating closely with a skilled team of engineers on ingesting signals and productionizing these models. If you're interested in building the state of art AI/ML solutions to unblock financial freedom for everyone, let's chat!