Staff Machine Learning Engineer (Research Scientist) - DFAI
Plaid offers a platform that enables applications to connect with users' bank accounts, facilitating a wide range of financial services. They provide tools for payments, personal finance management, credit, and more, serving clients like Moneybox, Western Union, and Affirm. Their core product is an API that provides access to a vast network of financial institutions, allowing developers to build financial products and services.
Funding
Projects
About Plaid
Plaid is a financial technology company that enables applications to connect with users' bank accounts. It allows consumers and businesses to interact with their bank accounts, check balances, and make payments through other financial technology applications. Plaid's network connects to over 12,000 financial institutions across 20 markets, serving a global user base of over 100 million. The company provides APIs for developers to build solutions for personal financial management, credit, payments, business finances, iGaming, and property management. Key products include Auth for account verification, Link for connecting accounts, Transactions for accessing financial data, Balance for real-time checks, Assets for verifying assets, and Identity for user verification. Plaid focuses on increasing conversion, fighting fraud, and providing clean, organized financial data for smarter underwriting and other financial services.
Skills
About the Role
You will lead the technical strategy and development of Plaid's foundation models, driving key decisions across pretraining objectives, model architecture, and fine-tuning approaches that power a wide range of downstream product applications. You will serve as the technical lead for the full machine learning lifecycle, overseeing everything from data curation and experimentation to production deployment, feature management, and observability. You will establish rigorous evaluation frameworks to measure model performance across diverse use cases and build scalable, repeatable pipelines that translate research into production impact. You will also partner closely with teams across the organization to define how products integrate with and adapt foundation models, enabling reusable ML infrastructure and reducing duplicated modeling efforts. As a senior technical leader, you will mentor engineers across experience levels, elevate engineering and experimentation standards, and communicate technical advancements both internally and externally as a representative of Plaid's AI and machine learning capabilities.
Requirements
- MS: 7–12+ years of industry experience with a demonstrated track record of technical leadership and production delivery
- PhD: 5–9+ years of industry experience with evidence of technical leadership (tech lead, principal/staff-equivalent roles) and end-to-end production ownership
- Prior technical leadership experience (tech lead, principal, or staff) with demonstrated cross-team influence and mentorship
- Deep expertise in Transformers/LLMs/Foundation Models, including large-scale training or domain adaptation
- End-to-end production ownership; proven track record shipping models through training, serving, monitoring, and iteration in live environments
- Distributed training experience and strong Python + software engineering fundamentals at a staff level
- Ability to drive technical alignment across teams: setting standards, defining integration patterns, and influencing beyond your immediate scope
- Fintech / financial data domain experience - Nice to have
- External publications or open-source contributions - Nice to have
- Experience defining ML platform capabilities (serving infra, feature stores) used across multiple teams - Nice to have
Responsibilities
- Own the end-to-end technical strategy for a foundation model built on one of the world's richest financial datasets, from pretraining architecture to production serving
- Do research that ships: drive decisions from experimentation through production systems that serve real customers and power multiple product teams
- Work across the full ML stack, including pretraining objectives, architecture design, distributed training, serving infrastructure, monitoring, and cross-team integration
- Set technical direction and mentor a high-caliber team, amplifying the capabilities of engineers and product teams across Plaid
- Help hundreds of millions of consumers achieve greater financial freedom through the ML capabilities you build and ship
Benefits
- Medical, dental, vision, and 401(k)