The Plaid Machine Learning Infrastructure (ML Infra) team is responsible for creating and maintaining the foundational systems, tools, and processes that enable efficient, scalable, reliable, responsible, and secure machine learning workflows for Plaid ML practitioners. The core ML Infra components and responsibilities cover core areas but are not limited to:
Feature Store Development: Developing a robust and efficient Feature Store platform customized for Plaid use cases to streamline feature engineering for both batch and real-time streaming features.Model Serving and Deployment: Developing and maintaining infrastructure and tools for deploying models into production with observability and low latency.Data Exploration and Experimentation: Using both vendor-based solutions, like Sagemaker Notebook, and in-house/open-source solutions, like ML-Flow and Trino, to support early model experimentation, model version monitoring, and tracking.ML Data Cost: Developing a creative framework to forecast, monitor, attribute, and track the cost for the end-to-end ML development life cycle.You will lead the machine learning Infra team to design and develop the Feature Store Platform for Plaid. You will support the team in setting the multi-year technical strategy and roadmap. You will maintain the current infrastructure for ML developer environment, ML model training, ML data feature creation/serving, ML model hosting/serving, ML model management, ML model service monitoring, vendor services (Tecton, OpenAI, Sagemaker, etc.), and the CI/CD pipelines/infrastructure deploying all assets.
You will also help pioneer the early foundation of the LLM AI platform for Plaid, working with MLEs and product engineers to support different ML-based product lines and collaborating with other Data Platform engineers to continuously improve the overall Plaid data ecosystems.
Responsibilities:Passionate about ML infrastructure and how it can solve real-world problems, especially in the fintech world.Both leading and hands-on contribution to building the Feature Store for the entire Plaid.Shape the future of the ML world for Plaid.Provide technical leadership in engineering excellence and mentorship.Qualifications:8+ years of software engineering experience.Extensive hands-on software engineering experience, with a strong track record of delivering successful projects within the ML Infrastructure or Platform domain at similar or larger companies.Deep understanding of high-quality ML Infrastructure systems, including Feature Stores, Training Infrastructure, Serving Infrastructure, and Model Monitoring.Experience in developing Feature Store systems.Strong cross-functional collaboration, communication, and project management skills, with proven ability to coordinate effectively.Demonstrated leadership abilities, including experience mentoring and guiding junior engineers.[Nice to have] Experience with AWS Sagemaker, Tecton, or LLM training/serving infra/platform. $182,520 - $297,000 a year
Target base salary for this role is between $182,520 and $297,000 per year. 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) the 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.
#J-18808-Ljbffr