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New York, New York, United States
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, Seattle, Washington D.C., Raleigh, London, and Amsterdam.
We’re part of Plaid’s Data organization, building models that help millions of people better understand and grow their financial lives. We apply machine learning to high-impact product challenges, working across product areas to develop solutions that create meaningful customer value.
We focus on credit, building models to the standards required in lending and supporting the next wave of cash-flow-based underwriting. We value technical expertise, creativity, user empathy, and teamwork, and we’re guided by Plaid’s principles of impact, growing together, openness and positivity, and inventing tomorrow.
As a Machine Learning Engineer on the Credit team, you’ll design, build, and deploy scalable machine learning solutions that support LendScore and the future of cash-flow-based underwriting. You’ll work across the full model lifecycle—from experimentation and offline training through production serving and monitoring—and partner with engineers and cross-functional teams to turn data and new modeling approaches into reliable systems.
In this role, you will:
Develop and productionize AI and machine learning models, from offline training through online serving and ongoing monitoring.
Experiment with modeling approaches and strategies for credit use cases, balancing model performance with the requirements of lending environments.
Partner with engineering teams to ingest signals and build the systems needed to bring models into production.
Contribute to both 0-to-1 problems and the scaling and improvement of established solutions.
Collaborate with teams across Plaid to help define the machine learning roadmap.
Dive into data and use evidence-based analysis to guide day-to-day decisions.
Building products that can empower millions of people through well-known and emerging fintech applications.
Experimenting with modern machine learning techniques on meaningful credit and lending problems.
Working across the full lifecycle of machine learning systems, from exploration to production and ongoing improvement.
Taking on both greenfield challenges and opportunities to scale solutions that are already delivering value.
Joining a high-ownership, bottom-up team where your work can shape the roadmap and drive business impact.
2+ years of experience training and serving AI or machine learning models in a production environment.
Experience in fintech lending and a strong understanding of how models are built and used in lending.
Experience building or working with data-intensive backend applications in large, distributed systems.
Ability to code and iterate independently using data infrastructure tools such as Python, Spark, Jupyter notebooks, and standard machine learning libraries.
A track record of taking ownership and 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: Experience in data analytics or data engineering.
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.
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.
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