Senior Machine Learning Engineer - Credit
Plaid offers a platform that enables applications to connect with users' bank accounts, facilitating a wide range of financial services. They provide tools for payments, personal finance management, credit, and more, serving clients like Moneybox, Western Union, and Affirm. Their core product is an API that provides access to a vast network of financial institutions, allowing developers to build financial products and services.
Funding
Projects
About Plaid
Plaid is a financial technology company that enables applications to connect with users' bank accounts. It allows consumers and businesses to interact with their bank accounts, check balances, and make payments through other financial technology applications. Plaid's network connects to over 12,000 financial institutions across 20 markets, serving a global user base of over 100 million. The company provides APIs for developers to build solutions for personal financial management, credit, payments, business finances, iGaming, and property management. Key products include Auth for account verification, Link for connecting accounts, Transactions for accessing financial data, Balance for real-time checks, Assets for verifying assets, and Identity for user verification. Plaid focuses on increasing conversion, fighting fraud, and providing clean, organized financial data for smarter underwriting and other financial services.
Skills
About the Role
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 have: 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
Benefits
- Equity
- Medical insurance
- Dental insurance
- Vision insurance
- 401(k)