Senior Machine Learning Engineer focused on building and deploying ML models into Plaid's financial products, working across the full ML lifecycle from experimentation to production scaling and monitoring. The role involves analyzing financial datasets, developing proof-of-concept solutions, and collaborating with product and engineering teams to integrate models and ensure their long-term performance and reliability.

Engineering Manager for Plaid's Network Enablement and Access (NEA) organization, focusing on leading a large engineering team (50+ engineers, 6 managers) through an AI transformation. The role involves setting engineering strategy, managing managers, owning technical direction for platforms including ML/data pipelines, and driving hiring. A key aspect is applying AI to engineering workflows and operational processes, with a push towards agentic systems for autonomous issue resolution. Experience leading AI transformations in engineering orgs and shipping data/insights products are nice-to-haves.

Plaid is seeking a Senior Software Engineer to build and operate the ML infrastructure that powers their AI-first strategy. This role focuses on designing and implementing scalable, reliable, and secure ML platforms, including feature stores, pipelines, deployment tooling, and inference systems, to accelerate the delivery of AI-powered financial products.

Data Scientist role at Plaid focused on expanding access, authorization, and usability of user financial footprints within a fintech consumer network. The role involves performing analyses, designing data models, building ML prototypes, defining OKRs, and analyzing experiments to drive product and business outcomes. Requires strong SQL, Python, and experience with data pipelines and ML prototyping.

Senior Data Scientist focused on building and operationalizing quality measurement and evaluation frameworks for AI/ML systems within Plaid's Data Foundation & AI team. The role involves defining metrics, investigating quality issues, automating workflows, and influencing roadmap decisions to ensure reliable and high-impact AI outcomes for customers.