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Plaid

Senior Machine Learning Engineer - Infra/Ops - Fraud

Plaid is hiring a Senior Machine Learning Engineer - Infra/Ops - Fraud for a remote role open to applicants in United States. It pays $229k-$315k a year and Level rates it ; you can apply on Plaid.

Level's read on this job

  • Level rates this machine learning engineer role Builds AI ●●●●: the job is building AI systems.
  • Pay on this posting starts 16% higher than the typical machine learning engineer posting on Level.
  • This is listed as a remote role.
  • The posting mentions PyTorch, SageMaker and Python among its tools and skills.
  • Plaid has 129 other open roles on Level.

AI in this role

Scale high-performance feature computation and online inference pipelines powering production machine learning fraud systems.

pytorchsagemakerpython
mlopsmachine-learning-infrastructurefraud-detectionpipeline-engineering

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.

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.

How we rate this

Senior Machine Learning Engineer - Infra/Ops - Fraud at Plaid rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

MLOpsMachine Learning InfrastructureFraud DetectionPipeline EngineeringPyTorchSageMakerPython

Also common in machine learning engineer jobs at this level

Pay

This job starts at
$229k
Typical machine learning engineer job
$197k

This posting starts 16% above the typical machine learning engineer job. See machine learning engineer jobs

Questions you could be asked

  1. Tell me about a project where mlops was part of your work. What did you do?
  2. Tell me about a project where machine learning infrastructure was part of your work. What did you do?
  3. Tell me about a project where fraud detection was part of your work. What did you do?
  4. Tell me about a project where pipeline engineering was part of your work. What did you do?
  5. Walk me through how you've used PyTorch in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: MLOps, Machine Learning Infrastructure, Fraud Detection, Pipeline Engineering, and PyTorch. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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