Plaid is transitioning into an AI-first organization, where data and machine learning drive the development of smarter, more secure insight products built on its extensive financial data network. At the heart of this transformation is the Machine Learning Infrastructure team, which creates the foundational platforms that support model experimentation, training, deployment, and monitoring at scale. These platforms include feature stores, data pipelines, deployment systems, and inference tools. The team is currently overhauling legacy systems, introducing a modern feature store, and defining a standardized ML Ops framework. Their goal is to empower product teams to deliver trustworthy insights more quickly, confidently deploy models, and enable the next generation of AI-driven financial tools.

As the Engineering Manager for Machine Learning Infrastructure, you will lead a team of experienced engineers in designing, building, and maintaining Plaid’s ML infrastructure. This role requires a leader with strong technical knowledge in ML infrastructure and a track record of managing and scaling senior engineering teams. You’ll be responsible for ensuring smooth execution, delivering high-quality systems, and collaborating closely with ML product teams to meet their needs. This is a hands-on leadership role focused on turning strategic goals into actionable outcomes, removing obstacles, and fostering a culture of accountability and technical excellence.

Responsibilities:

– Lead and support the ML Infrastructure team, ensuring timely and successful project execution.
– Develop and launch a next-generation feature store to enhance the speed and reliability of model development.
– Define and promote a standardized ML Ops workflow for secure and scalable model training, deployment, and monitoring.
– Maintain high operational standards for ML pipelines, deployment systems, and inference tools.
– Collaborate with ML product teams to understand their needs and deliver solutions that accelerate model development and iteration.
– Hire, mentor, and grow engineering talent while cultivating a collaborative, high-performing team environment.

Qualifications:

– 8–10 years of experience in ML infrastructure, including hands-on engineering roles.
– At least 2 years of experience managing infrastructure or ML platform engineering teams.
– Proven ability to build and operate ML or AI infrastructure at scale.
– Strong technical expertise across ML/AI infrastructure areas such as feature stores, pipelines, deployment, inference, and observability.
– Demonstrated success in leading complex technical projects involving multiple stakeholders.
– Excellent communication and stakeholder management skills.

Salary Range: $241,200 – $400,000 annually (Zone 1: New York City and San Francisco Bay Area)

Compensation may also include equity and/or commission, depending on the role. Plaid offers a comprehensive benefits package, including medical, dental, vision, and 401(k). Salary and benefits are determined by factors such as job responsibilities, candidate experience and skills, and location, and may change in accordance with company policies.