Senior Machine Learning Engineer - Credit

Plaid•San Francisco, CA

25d

About The Position

Plaid's Data team is building models that improve how millions of users understand and grow their financial lives. We’re looking for machine learning engineers with experience applying state-of-the-art machine learning and modeling techniques, including natural language processing, anomaly detection, optimization, and time series forecasting, across different product areas. We value not only technical know-how, but also creativity, user empathy, and teamwork. You’ll be a machine learning engineer in the Data org, contributing to diverse, high-impact machine learning challenges. In this role, you’ll focus on designing, building, and deploying scalable ML solutions and systems within the credit environment. You’ll lead experimentation with new modeling approaches and strategies, collaborate closely with engineers on ingesting signals and productionizing models, and help build the next wave of cash flow based underwriting. You’ll own AI and machine learning work across the full model lifecycle, from offline training to online serving and monitoring, while helping define the ML roadmap with cross-functional teams.

Requirements

6+ years of experience training and serving AI and machine learning models in a production environment
Experience in fintech lending, with a strong understanding of how models are built in that space
Experience building or working with data-intensive backend applications in large distributed systems
Ability to code and iterate independently using tools such as Python, Spark, Jupyter notebooks, and standard machine learning libraries
Strong ownership mindset and a track record of driving projects to business impact
Ability to work effectively with both technical and non-technical teams
Master’s degree or equivalent work experience in Computer Science, Mathematics, Engineering, or a closely related field

Nice To Haves

data analytics and data engineering experience

Responsibilities

Build machine learning systems that empower millions of users through well-known and emerging fintech applications with access to financial services
Experiment with cutting-edge machine learning modeling techniques across high-impact credit use cases
Work on both 0-1 stage problems and scaling systems from 1-10
Develop AI and machine learning models across the full lifecycle, from offline training to online serving and monitoring
Design, build, and deploy scalable ML solutions and systems in a production environment
Collaborate with teams across Plaid to define the machine learning roadmap
Dive deep into data and apply data-driven decision-making in day-to-day work
Operate with high ownership on a bottom-up driven team