Plaid

Plaid is seeking a Senior Research Scientist to lead applied research on their foundation model, focusing on designing architectures, pretraining objectives, and fine-tuning strategies. The role involves building and maintaining end-to-end production ML systems, including training pipelines, model serving, feature engineering, and monitoring, with a strong emphasis on shipping models to production and developing robust evaluation frameworks.

Plaid is building a new AI Applications team to scale their GenAI-powered products and features, focusing on integrating AI into financial services for customer experience, identity verification, and fraud prevention. The role involves full-stack development, architecting GenAI solutions, and rapid experimentation.

Staff Software Engineer role focused on building and scaling AI applications within Plaid's FinTech ecosystem. The role involves developing integration patterns for AI providers, enhancing conversational AI interfaces, architecting trust layers for agentic commerce, and extending AI-powered customer experience agents. This includes working with multi-turn, multi-agent systems, RLHF, and customer-specific memory, as well as expanding agents to support product recommendation, onboarding, and upselling.

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.

Senior Fraud Researcher at Plaid, focusing on using financial network data, transaction patterns, and device signals to detect and prevent fraud. The role involves leading investigations, translating findings into detection improvements, and collaborating with Data Science, ML/AI, and Product teams to shape fraud capabilities. It emphasizes applied research, signal utilization, and ecosystem monitoring to stay ahead of adversaries, directly driving features, model inputs, and product design.

Staff Product Manager for Plaid's AI Foundations team, responsible for defining the strategy and roadmap for the core AI and data layer. This role involves building scalable AI systems from embeddings and representation learning to applied model integrations, partnering with Engineering and Data Science to drive initiatives from concept to production, and ensuring responsible AI practices.

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.