Plaid is evolving into an AI-first company, and the Machine Learning Infrastructure team needs to build the platforms that enable model developers to experiment, train, deploy, and monitor machine learning systems reliably and at scale. This includes replacing legacy systems with a modern feature store and establishing a standardized ML Ops “golden path” to enable Plaid’s product teams to move faster with trustworthy insights, deploy models with confidence, and unlock the next generation of AI-powered financial experiences.
Requirements
- 8–10 years of experience in ML infrastructure, including direct hands-on expertise as an engineer, IC/TL.
- Proven experience delivering and operating ML or AI infrastructure at scale.
- Solid technical depth across ML/AI infrastructure domains (e.g., feature stores, pipelines, deployment, inference, observability).
- 2+ years of experience managing infrastructure or ML platform engineers.
- Demonstrated ability to drive execution on complex technical projects with cross-team stakeholders.
Responsibilities
- Build and launch Plaid’s next-generation feature store to improve reliability and velocity of model development.
- Define and drive adoption of an ML Ops “golden path” for secure, scalable model training, deployment, and monitoring.
- Ensure operational excellence of ML pipelines, deployment tooling, and inference systems.
- Partner with ML product teams to understand requirements and deliver solutions that accelerate model development and iteration.
- Lead and support the ML Infra team, driving project execution and ensuring delivery on key commitments.
- Translate strategy into action, remove blockers, and build a culture of ownership and technical excellence.
Other
- Lead and support the ML Infra team, driving project execution and ensuring delivery on key commitments.
- Recruit, mentor, and develop engineers, fostering a collaborative and high-performing team culture.
- Strong communication and stakeholder management skills.
