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# Senior Machine Learning Engineer (Research Scientist) - Data Foundation & AI

- **Company:** Plaid Inc.
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Infrastructure, Distributed Computing Environment, Machine Learning, Feature Engineering, Large Language Models, Free and Open-Source Software, Machine Learning Operations, Feature Extraction
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-machine-learning-engineer-research-scientist-data-foundation-ai-san-francisco-ca--f682ba38-8519-45e8-8ac9-84e2b7dff086

## About the Role

* Strong applied ML research skills with production delivery experience.
 * Depth in Transformers/LLMs, representation learning, or large-scale model training.
 * Demonstrated ability to ship models to production (not just prototype).
 * Distributed training experience and strong Python+ software engineering fundamentals.
 * Fintech / financial data domain experience is a plus.
 * External publications or open-source contributions is a plus.

## Description

As a Senior Research Scientist on the Data Foundation and AI team, you will lead applied research on Plaid's foundation model by designing model architectures, pretraining objectives, and fine-tuning strategies that generalize across a wide range of downstream product use cases. You will also build and maintain end-to-end production machine learning systems, including training pipelines, model serving infrastructure, feature engineering, and monitoring. In addition, you will develop robust evaluation frameworks to assess model performance across diverse tasks, ensuring quality beyond single-metric optimization., * Building a foundation model on one of the world's richest financial datasets that no one else has.

 * Doing research that ships: moving from experimentation and prototypes to production systems serving real customers.
 * Working across the full ML stack, from pretraining objectives and architectures to serving infrastructure and monitoring.
 * Collaborating with a high-caliber team and seeing your work amplify the capabilities of multiple product teams.
 * Helping hundreds of millions of consumers achieve greater financial freedom through data-driven products.