Senior Machine Learning Engineer Embedded Insights
Plaid is a financial data network and fintech infrastructure company that helps people securely connect financial accounts to digital financial services.
Maintainer signals as of 9/2/2026
Funding history
Projects
About Plaid Inc.
Plaid provides developer infrastructure and financial tools for account connectivity, financial data access, bank payments, identity verification, AML monitoring, credit and underwriting, and fraud prevention. Its network supports thousands of fintech companies and more than 12,000 financial institutions across the United States, Canada, the United Kingdom, and Europe.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will build machine learning features for a consumer-facing product, translate business needs into machine learning problems, iterate toward product-market fit, and define success metrics. You will validate opportunities, productionize models, develop feedback loops, optimize and monitor models, and communicate technical decisions clearly.
Requirements
- 6+ years of machine learning experience.
- Experience deploying models into customer-facing systems.
- Experience identifying, defining, and proposing machine learning opportunities.
- Ability to analyze large and complex financial datasets.
- Experience taking machine learning systems from experimentation through production and ongoing improvement.
- Proficiency in SQL, Python, data visualization, and analysis tools.
- Ability to communicate complex technical systems and decisions to cross-functional partners.
Responsibilities
- Build machine learning-based features for a consumer-facing product.
- Translate business requirements into machine learning problems and influence product strategy.
- Iterate and experiment to drive product-market fit.
- Define success metrics and guardrails for machine learning features.
- Build data feedback loops with machine learning engineers.
- Analyze datasets and complete proofs of concept for machine learning opportunities.
- Productionize and deploy models in customer-facing products.
- Develop features, retraining cadences, metrics, alerts, and dashboards to maintain model health.
- Communicate technical decisions, tradeoffs, and system behavior to partners.
Benefits
- Equity
- Medical insurance
- Dental insurance
- Vision insurance
- 401(k)
