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 & AI team builds advanced ML/AI models and applications that enable product teams to deliver intelligence at scale. We design infrastructure and abstractions that make AI development faster, more reliable, and more impactful. From embeddings and representation learning to applied AI systems, our work provides the building blocks for the next generation of financial services on Plaid.
You’ll be a senior machine learning engineer on the Data Foundation & AI team. In this role, you will design, build, and scale advanced ML/AI systems that power Plaid products and applications. Your work may span developing reliable distributed training and serving systems, improving ML operations at scale, and building AI-powered applications that enable new product experiences.
The Data Foundation & AI team builds advanced ML/AI models and applications that enable product teams to deliver intelligence at scale. We design infrastructure and abstractions that make AI development faster, more reliable, and more impactful. From embeddings and representation learning to applied AI systems, our work provides the building blocks for the next generation of financial services on Plaid.You’ll be a senior machine learning engineer on the Data Foundation & AI team. In this role, you will design, build, and scale advanced ML/AI systems that power Plaid products and applications. Your work may span developing reliable distributed training and serving systems, improving ML operations at scale, and building AI-powered applications that enable new product experiences.
The target base salary for this position ranges from $225,600/year to $337,200/year in Zone 1. The target base salary will vary based on the job's location.
Our geographic zones are as follows:
Zone 1 - New York City and San Francisco Bay Area
Zone 2 - Los Angeles, Seattle, Washington D.C.
Zone 3 - Austin, Boston, Denver, Houston, Portland, Sacramento, San Diego
Zone 4 - Raleigh-Durham and all other US cities
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.
Responsibilities
Building and scaling advanced ML/AI systems that power core Plaid products and applications used by millions of consumers.
Driving impact at scale by improving distributed training, serving, and ML operations to make Plaid’s AI capabilities faster, more reliable, and more widely available.
Developing new AI applications that enable innovative product experiences across fintech.
Tackling 0 to 1 problems where you explore new approaches, as well as scaling 1 to 10 systems for reliability and efficiency.
Collaborating with some of the strongest MLEs at Plaid in a high-ownership, bottom-up driven team.
Experimenting with cutting-edge ML and AI techniques while balancing practical productionization and measurable business impact.
Qualifications
5+ years of experience training, deploying, and scaling ML/AI models in production environments.
Strong experience with distributed systems and ML operations — from large-scale training to low-latency serving and monitoring.
Proficiency in Python and modern ML frameworks (e.g., PyTorch), with the ability to implement and optimize complex models.
Hands-on experience building or scaling ML/AI infrastructure, pipelines, or reusable platforms that support multiple teams.
Curiosity and drive to experiment with advanced AI techniques (e.g., embeddings, retrieval, generative modeling) while staying grounded in production impact.
Experience applying ML/AI in fintech or similarly regulated industries is a plus.
Ability to thrive in a collaborative environment, working with both technical and non-technical partners to drive measurable outcomes.
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 [email protected].
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