Experienced Machine Learning Modeler - Payments

San Francisco
Engineering – Engineering /
Full-time /
Hybrid
We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. #LI-Hybrid

Plaid’s Machine Learning 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 -- toward different product areas. We value not only technical know-how, but also creativity, user empathy, and teamwork.

You will be a machine learning modeler on the payments team focused on building and maintaining machine learning models to power products and platforms.

Responsibilities

    • Hands-on develop, productionize, and operate Machine Learning models and pipelines to improve a diverse range of Plaid products.
    • Continuously proposing and developing new features to improve the AI/ML model performance. 
    • Working with the ML infrastructure team to improve ML infrastructure that powers the end-to-end ML development lifecycle.  
    • Debugging ML production issues and ensuring stable model serving.
    • Work collaboratively with cross-functional partners to identify opportunities for business impact, understand, refine, and prioritize requirements for AI/ML models, drive engineering decisions, and quantify impact.

Qualifications

    • 5+ years of engineering experience.
    • Proficiency in machine learning algorithms and solid understanding of mathematics and statistics. 
    • Experience in developing end to end data systems/products and productionizing AI/ML models.
    • Experience in well-known big data processing infrastructures, like Spark, Airflow, DBT, Hive, Presto, and etc.
    • Ability to architect software and ML systems at scale.
    • Solid software engineer skill in complex and multi-language systems. Code fluency in Python.
    • Experience in working with product, design, and backend engineering.
$203,040 - $303,480 a year
Target base salary for this role is between $203,040 and $303,480 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) 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.
Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid! Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com. Please review our Candidate Privacy Notice here.

Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!

Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.

Please review our Candidate Privacy Notice here.