Staff Machine Learning Engineer - Fraud Data Job at Plaid Inc in New York
Plaid Inc, New York, NY, 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, Washington D.C., London and Amsterdam.
The Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s cutting-edge fraud detection products. By leveraging Plaid’s extensive network data, we enable proactive fraud prevention—stopping fraud before it happens. Our team owns the entire ML lifecycle, from developing feature pipelines and training models to deploying and monitoring them in production. We ensure that our systems scale reliably and efficiently as Plaid continues to grow and support hundreds of customers.
As a Staff Machine Learning Engineer on Plaid’s Fraud Data team, you will design and build scalable ML infrastructure that powers our industry-leading fraud detection product. You’ll lead the evolution of our model deployment, monitoring, and observability frameworks to ensure high reliability and performance at scale. Collaborating closely with teams across ML Infrastructure, Product, and Engineering, you’ll deliver robust systems that protect users and customers from fraud. In addition, you’ll mentor other engineers and help shape the long-term technical vision and strategy of the Fraud Data team.
We are open to remote candidates for this role.
Responsibilities
Design and build scalable ML infrastructure for Plaid’s fraud detection product.
Work in a fast-pace environment to build a rapidly growing product with a championship team.
Solve complex problems at the intersection of ML systems, data, and reliability.
Build the foundations for fraud detection on the largest financial dataset in the world.
Collaborate with talented engineers and data scientists across Plaid.
Qualifications
8+ years total experience, with at least 5 years building and deploying production ML systems.
Proven experience in machine learning infrastructure/operations.
Demonstrated technical leadership and architectural vision, driving systems from concept to production.
Proficiency in Python, PyTorch, Spark, SageMaker, and Airflow, or equivalent technologies.
Nice to have - experience working in fraud detection, risk modeling, or financial security domains.
Nice to have - background in graph machine learning or related techniques.
$253,200 - $400,000 a year
Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!
Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.
Please review our Candidate Privacy Notice here.
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In Summary: Plaid powers the tools millions of people rely on to live a healthier financial life . The Fraud Data team builds the machine learning systems that power Plaid’s cutting-edge fraud detection products . You will design and build scalable ML infrastructure that powers our industry-leading fraud detection product .
En Español: Creemos que la forma en que las personas interactúan con sus finanzas mejorará drásticamente en los próximos años. Estamos dedicados a empoderar esta transformación mediante la construcción de herramientas y experiencias que miles de desarrolladores utilizan para crear sus propios productos. Plaid potencia las herramienta que millones de personas confían en vivir una vida financiera más saludable. Trabajamos con miles de compañías como Venmo, SoFi, varias de las Fortune 500 y muchos de los bancos más grandes para facilitar que la gente conecte sus cuentas financieras con las aplicaciones y servicios que deseen usar. La red de Plaids cubre 12,000 instituciones financieras de Estados Unidos, Canadá, Reino Unido y Europa. Fundada en 2013, la compañía tiene su sede en San Francisco con oficinas en Nueva York, Washington D.C., Londres y Ámsterdam. Dirigirá la evolución de nuestros marcos de implementación, monitoreo y observabilidad de modelos para garantizar una alta fiabilidad y rendimiento a escala. Además, asesorará a otros ingenieros y ayudará a dar forma a la visión técnica y estrategia a largo plazo del equipo de datos fraudulentos. Estamos abiertos a candidatos remotos para este papel. Responsabilidades Diseñar y construir una infraestructura ML escalable para el producto de detección de fraude Plaids. Trabajar en un entorno acelerado para construir un producto que crece rápidamente con un equipo campeón. Resolver problemas complejos en la intersección de sistemas ML, datos y fiabilidad. Construir las bases para detectar fraudes en el conjunto de datos financieros más grande del mundo. Colaborar con ingenieros talentosos y científicos de datos de todo Plaid. Qualificaciones 8+ años de experiencia total, con al menos 5 años construyendo e implementando sistemas de aprendizaje automático. Experiencia probada en infraestructuras / operaciones de producción. Reconocemos que las calificaciones sólidas pueden provenir tanto de experiencias laborales anteriores como de experiencia vivida. Le animamos a aplicar para un puesto incluso si su experiencia no coincide plenamente con la descripción del trabajo. Siempre estamos buscando miembros del equipo que traigan algo único a Plaid! Plaid se enorgullece de ser un empleador de igualdad de oportunidades y valora la diversidad en nuestra empresa. No discriminamos por raza, color, origen nacional, etnia, religión o creencia religiosa, sexo (incluyendo embarazo, parto o condiciones médicas relacionadas), orientación sexual, género, identidad de género , expresión de géneros, estatus transgénero, estereotipos sexuales, edad, estado militar o veterano, discapacidad u otras características legalmente protegidas aplicables. También consideramos candidatos cualificados con antecedentes penales, consistentes con las leyes federales, estatales y locales aplicables. Plaid es proporcionar acomodaciones razonables para los candidatos con discapacidades en nuestro proceso de reclutamiento. Si usted necesita ayuda, consulte nuestras entrevistas al número #JB-Lr1880, pléase nos permita revisar cualquier incapacidad debido a sus solicitudes.
The Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s cutting-edge fraud detection products. By leveraging Plaid’s extensive network data, we enable proactive fraud prevention—stopping fraud before it happens. Our team owns the entire ML lifecycle, from developing feature pipelines and training models to deploying and monitoring them in production. We ensure that our systems scale reliably and efficiently as Plaid continues to grow and support hundreds of customers.
As a Staff Machine Learning Engineer on Plaid’s Fraud Data team, you will design and build scalable ML infrastructure that powers our industry-leading fraud detection product. You’ll lead the evolution of our model deployment, monitoring, and observability frameworks to ensure high reliability and performance at scale. Collaborating closely with teams across ML Infrastructure, Product, and Engineering, you’ll deliver robust systems that protect users and customers from fraud. In addition, you’ll mentor other engineers and help shape the long-term technical vision and strategy of the Fraud Data team.
We are open to remote candidates for this role.
Responsibilities
Design and build scalable ML infrastructure for Plaid’s fraud detection product.
Work in a fast-pace environment to build a rapidly growing product with a championship team.
Solve complex problems at the intersection of ML systems, data, and reliability.
Build the foundations for fraud detection on the largest financial dataset in the world.
Collaborate with talented engineers and data scientists across Plaid.
Qualifications
8+ years total experience, with at least 5 years building and deploying production ML systems.
Proven experience in machine learning infrastructure/operations.
Demonstrated technical leadership and architectural vision, driving systems from concept to production.
Proficiency in Python, PyTorch, Spark, SageMaker, and Airflow, or equivalent technologies.
Nice to have - experience working in fraud detection, risk modeling, or financial security domains.
Nice to have - background in graph machine learning or related techniques.
$253,200 - $400,000 a year
Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!
Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.
Please review our Candidate Privacy Notice here.
#J-18808-Ljbffr
In Summary: Plaid powers the tools millions of people rely on to live a healthier financial life . The Fraud Data team builds the machine learning systems that power Plaid’s cutting-edge fraud detection products . You will design and build scalable ML infrastructure that powers our industry-leading fraud detection product .
En Español: Creemos que la forma en que las personas interactúan con sus finanzas mejorará drásticamente en los próximos años. Estamos dedicados a empoderar esta transformación mediante la construcción de herramientas y experiencias que miles de desarrolladores utilizan para crear sus propios productos. Plaid potencia las herramienta que millones de personas confían en vivir una vida financiera más saludable. Trabajamos con miles de compañías como Venmo, SoFi, varias de las Fortune 500 y muchos de los bancos más grandes para facilitar que la gente conecte sus cuentas financieras con las aplicaciones y servicios que deseen usar. La red de Plaids cubre 12,000 instituciones financieras de Estados Unidos, Canadá, Reino Unido y Europa. Fundada en 2013, la compañía tiene su sede en San Francisco con oficinas en Nueva York, Washington D.C., Londres y Ámsterdam. Dirigirá la evolución de nuestros marcos de implementación, monitoreo y observabilidad de modelos para garantizar una alta fiabilidad y rendimiento a escala. Además, asesorará a otros ingenieros y ayudará a dar forma a la visión técnica y estrategia a largo plazo del equipo de datos fraudulentos. Estamos abiertos a candidatos remotos para este papel. Responsabilidades Diseñar y construir una infraestructura ML escalable para el producto de detección de fraude Plaids. Trabajar en un entorno acelerado para construir un producto que crece rápidamente con un equipo campeón. Resolver problemas complejos en la intersección de sistemas ML, datos y fiabilidad. Construir las bases para detectar fraudes en el conjunto de datos financieros más grande del mundo. Colaborar con ingenieros talentosos y científicos de datos de todo Plaid. Qualificaciones 8+ años de experiencia total, con al menos 5 años construyendo e implementando sistemas de aprendizaje automático. Experiencia probada en infraestructuras / operaciones de producción. Reconocemos que las calificaciones sólidas pueden provenir tanto de experiencias laborales anteriores como de experiencia vivida. Le animamos a aplicar para un puesto incluso si su experiencia no coincide plenamente con la descripción del trabajo. Siempre estamos buscando miembros del equipo que traigan algo único a Plaid! Plaid se enorgullece de ser un empleador de igualdad de oportunidades y valora la diversidad en nuestra empresa. No discriminamos por raza, color, origen nacional, etnia, religión o creencia religiosa, sexo (incluyendo embarazo, parto o condiciones médicas relacionadas), orientación sexual, género, identidad de género , expresión de géneros, estatus transgénero, estereotipos sexuales, edad, estado militar o veterano, discapacidad u otras características legalmente protegidas aplicables. También consideramos candidatos cualificados con antecedentes penales, consistentes con las leyes federales, estatales y locales aplicables. Plaid es proporcionar acomodaciones razonables para los candidatos con discapacidades en nuestro proceso de reclutamiento. Si usted necesita ayuda, consulte nuestras entrevistas al número #JB-Lr1880, pléase nos permita revisar cualquier incapacidad debido a sus solicitudes.