Senior Machine Learning Engineer (Research Scientist) - DFAI

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, Washington D.C., London and Amsterdam. The Data Foundation and AI team within Plaid’s Data organization builds the shared machine learning and AI infrastructure that powers capabilities across Plaid’s product suite. Our team transforms Plaid’s unique financial network data into scalable, general-purpose representations that can be leveraged by teams throughout the company. We own the full lifecycle of these systems, from pretraining data curation and model development to production serving, evaluation, and monitoring, enabling reliable and impactful AI-driven experiences at scale. As a Senior Research Scientist, you will lead applied research efforts for Plaid’s foundation model, designing model architectures, pretraining objectives, and fine-tuning strategies that generalize across a wide range of downstream product use cases. You will build and maintain production-grade ML systems end-to-end, including training pipelines, model serving infrastructure, feature engineering workflows, and monitoring systems. You will develop robust evaluation frameworks that measure model quality across diverse tasks and real-world applications, rather than optimizing for a single benchmark metric. In close partnership with product and engineering teams across Plaid, you will adapt foundation models to specific business needs and validate their impact through rigorous experimentation. You will also communicate and publish research findings internally and externally, helping advance the state of machine learning and AI across the organization. Responsibilities: - 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. Requirements: - MS or PhD in ML/AI/CS/Stats/Applied Math (or closely related). PhD preferred but not required — candidates with equivalent industry research and production experience will be considered. - 3-7 years of industry experience building and deploying ML models, with evidence of both research depth and production delivery. - 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 - Nice to have - External publications or open-source contributions - Nice to have 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 appl