Senior Machine Learning Engineer - Infra/Ops - Fraud

Plaid
New York City Office +2 more
Hybrid

In the 12 months to 30 Jun 2026, Plaid filed 2 H-1B positions titled "Machine Learning Engineer". Source: U.S. Department of Labor, LCA disclosure data. A record of filings already made, not a commitment to sponsor.

Who this role is best for

Best suited to candidates with 6+ years of experience in ML infrastructure and operations, working in the fraud detection domain.

Best fit for

  • Candidates with 6+ years of experience in deploying and scaling production ML systems
    — “6+ years of relevant experience, with a strong focus on building, deploying, and scaling production machine learning systems.”
  • Professionals with strong technical skills in Python and ML/data technologies
    — “Proficiency with Python and experience with ML and data technologies such as PyTorch, Spark, SageMaker, and Airflow.”
  • Candidates with a background in fraud detection or risk domains
    — “Experience in fraud or risk domains.”

Things to consider

  • The position demands a strong focus on system reliability and observability in production ML systems.
    — “build robust observability, monitoring, and automated debugging capabilities”

How to stand out

  • Highlight experience with end-to-end ML system development and deployment in your resume and interviews.
    — “Proven ability to independently own and deliver complex, end-to-end machine learning engineering projects.”
  • Showcase your ability to build scalable and reliable systems in fast-paced environments.
    — “Build and scale machine learning systems that power a rapidly growing fraud detection product in a fast-paced environment.”
  • Demonstrate your understanding of leveraging financial network data for fraud detection.
    — “Develop foundational ML capabilities that leverage Plaid’s extensive financial network data to detect and prevent fraud.”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Developed high-performance feature computation and online inference pipelines
  • Built robust observability and monitoring capabilities
  • Delivered scalable, high-impact ML solutions
Typical background
6+ years of relevant experience in building, deploying, and scaling production machine learning systems

Skills & requirements

Required

PythonML Infrastructure And OperationsProduction Deployment And MonitoringFeature Pipelines And Model TrainingOnline Inference PipelinesObservability And MonitoringAi-assisted ToolsCollaboration With ML Infrastructure, Data Science, And Product Teams

Preferred

Fraud DetectionGraph Machine Learning

Stack & domain

PythonPyTorchSparkSagemakerAirflowLeadershipCommunicationFraud DetectionMachine LearningData InfrastructureProduction Reliability

About the role

Original posting from Plaid via Ashby

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 intersection of machine learning, data infrastructure, and production reliability.
  • Develop foundational ML capabilities that leverage Plaid’s extensive financial network data to detect and prevent fraud.
  • Collaborate closely with engineers, data scientists, and cross-functional partners across Plaid to deliver high-impact solutions.

Qualifications:

  • 6+ years of relevant experience, with a strong focus on building, deploying, and scaling production machine learning systems.
  • Strong experience with ML infrastructure and operations, including production deployment, monitoring, and reliability.
  • Proven ability to independently own and deliver complex, end-to-end machine learning engineering projects.
  • Proficiency with Python and experience with ML and data technologies such as PyTorch, Spark, SageMaker, and Airflow.

Nice-to-Have:

  • Experience in fraud or risk domains.
  • Experience in Graph machine learning.

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 https://plaid.com/legal/#candidate-privacy-notice.

Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.

Source: Plaid careers (Ashby)

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