Role Overview
Plaid is hiring a entry-level Machine Learning Engineer - (Payment Risk/Fraud) - Embedded Insights. This is a full-time remote role, with the team based in San Francisco HQ. Part of Plaid's Lifecycle hiring, posted 4 days ago. Full responsibilities, required qualifications, and the apply link are listed in the description below.
Salary Context
Salary is not disclosed in this posting. Market median for Junior-level Lifecycle roles is $82k-$108k (based on 27 comparable listings). Many employers share specifics during the interview process or after an initial screen.
Resume Keywords to Include
Make sure these keywords appear in your resume to improve ATS scoring
Job description
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.
The Embedded Insights team supports Plaid’s mission to build a world-class suite of intelligence products. We identify the best opportunities to use machine learning in Plaid products, prove out those opportunities, and collaborate with cross-functional partners to turn them into real world production systems.
As a Machine Learning Engineer on the Embedded Insights team, you will drive machine learning initiatives from concept to production, working across the full model development lifecycle. You will leverage Plaid’s unique datasets to identify high-impact opportunities for machine learning, develop proofs of concept to validate new approaches, and build MVP solutions that demonstrate customer value. Partnering closely with product managers, engineers, and other cross-functional stakeholders, you will embed within product teams to translate successful prototypes into scalable, customer-facing products. As solutions gain traction, you will help expand their reach by optimizing models for new use cases, improving system scalability, and incorporating customer feedback gathered before and after launch. You will also be responsible for maintaining and enhancing existing machine learning systems through feature development, retraining strategies, and robust monitoring frameworks, including metrics, alerts, and dashboards that ensure model performance, reliability, and long-term health.
Responsibilities
- Opportunity to shape Plaid’s future as a company where intelligence products are a core value proposition.
- Dive into one of the most unique datasets available in the industry and shape the strategy to leverage its value.
- Work across many different areas and learn deeply about the entire Plaid product suite
- Build products that empower millions of people to achieve financial freedom and opportunity.
- Work closely with customers to ensure products meet their needs and demonstrate true impact.
- Join a high ownership team where the greenfield opportunity is extremely high.
Qualifications
- 2+ years of experience in machine learning, including deploying machine learning models into real-world, customer facing systems.
- Payment risk, fraud or trust & safety experience.
- High agency and creativity; experience identifying, defining, and proposing high impact machine learning opportunities.
- Ability to analyze large and complex financial datasets to derive insights.
- Advanced degree or equivalent work experience in Statistics, Economics, Mathematics, Data Science, or a related field.
- Proficiency in SQL, Python, and data visualization/analysis tool.
- Ability to clearly communicate complex technical systems and decision making.
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 https://plaid.com/legal/#candidate-privacy-notice.
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.
About Plaid

Plaid
plaid.com
92 other open roles at Plaid on TryApplyNow.
Frequently Asked Questions
How do I apply for the Machine Learning Engineer - (Payment Risk/Fraud) - Embedded Insights position at Plaid?
Use the Apply button above to submit your application directly to Plaid. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Is the Machine Learning Engineer - (Payment Risk/Fraud) - Embedded Insights role at Plaid remote?
Yes. This is a remote role. The team is based in San Francisco HQ, but the position itself does not require relocating to that office.
What does a Machine Learning Engineer - (Payment Risk/Fraud) - Embedded Insights at Plaid earn?
Plaid has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.
When was the Machine Learning Engineer - (Payment Risk/Fraud) - Embedded Insights role at Plaid posted?
This role was posted on July 6, 2026 (4 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
Is the Machine Learning Engineer - (Payment Risk/Fraud) - Embedded Insights role at Plaid entry-level?
Yes. This is an entry-level position. Strong candidates typically have 0-2 years of relevant work experience, internships, or significant project work. Read the full description for any specific qualification requirements Plaid has listed.
Similar Jobs
More Jobs at Plaid
View all →Account Manager - SMB
Plaid
Senior Data Scientist - Network Value
Plaid
Sales Lead - This Week in Fintech
Plaid
Executive Assistant, Revenue & Partnerships
Plaid
Business Development Representative - Banking & Wealth
Plaid
AI-powered job search
Get every job scored to your resume
Upload your resume and get jobs ranked, your resume tailored, and employee contacts found automatically.
Get started freeNo credit card to start