Machine Learning Engineer (Research Scientist) - DFAI

Plaid

Quick summary

Work type
On-site
Location
San Francisco, CASeattle, WANew York, NY
Salary
$211,680–$272,160 / yr
Posted
2 days ago

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $225k
This role $242k
$161k most similar roles pay here $284k

This role pays more than 63% of similar roles. Most pay $197,925–$252,887 — the shaded band above. At the midpoint, this role pays about $242k versus about $225k for comparable roles.

Based on 240 similar postings.

Employer

About Plaid

Plaid is a financial technology company that builds a data network powering digital finance applications, enabling consumers to securely connect their financial accounts to apps and services. Industry: Financial Technology & Data Infrastructure

Plaid currently has 98 open roles on FindRole.

Listed pay typically runs $190,800–$262,800 across 98 roles with salary data.

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At a glance

TL;DR · Machine Learning Engineer (Research Scientist) - DFAI

As a Research Scientist on Plaid’s Data Foundation & AI team, you will develop novel model architectures and pretraining objectives to enhance the company's foundation models for financial applications. Your day-to-day involves working across the entire machine learning stack, from data engineering and training pipelines to serving infrastructure and monitoring systems, ensuring reliable AI capabilities at scale. You will collaborate closely with product and engineering teams to adapt these models to solve specific business challenges, validate their impact through rigorous experimentation, and translate research advances into production-ready solutions. The role requires a strong background in machine learning, including experience with Transformers/LLMs, representation learning, and distributed training, as well as proficiency in Python and software engineering fundamentals. This position offers the opportunity to work on one of the world’s richest financial datasets, contributing to Plaid's mission of empowering hundreds of millions of consumers through data-driven products.

What you'll do

  • Develop novel model architectures and pretraining objectives for financial data.
  • Adapt foundation models to solve specific business challenges in finance.
  • Design comprehensive evaluation frameworks for diverse tasks and use cases.
  • Move research from experimentation to production systems serving real customers.
  • Work across the full ML stack, including training pipelines and monitoring.

What we're looking for

  • MS or PhD in ML/AI/CS/Stats/Applied Math with industry research and production experience.
  • 1-3 years of industry experience building and deploying machine learning models.
  • Strong applied ML research skills with proven ability to deliver production systems.
  • Expertise in Transformers, LLMs, representation learning, and large-scale model training.
  • Experience with distributed training and solid Python programming and software engineering skills.
  • Ability to move from experimentation to shipping production-ready machine learning models.

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