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Plaid is seeking a Senior Machine Learning Engineer to join the Embedded Insights team in New York. You will help shape Plaid's future by building machine learning-powered products and features, initially supporting the Plaid App—a 0-to-1 consumer-facing product. You will work closely with product managers, data scientists, engineers, and customers to translate ambiguous opportunities into effective ML systems that create measurable customer value.
In this role, you will build machine learning-based features for a new consumer-facing product, partner with product managers to translate business requirements into ML problems and influence product strategy, rapidly iterate and experiment to drive product-market fit, work with data scientists to define success metrics and guardrails, and partner with other MLEs to build effective data feedback loops.
As a member of the broader Embedded Insights team, you will analyze Plaid's unique financial datasets to identify high-impact ML opportunities and complete proofs of concept, embed with product teams to productionize models and deploy them in customer-facing products, optimize and maintain model health through feature development and performance monitoring, and communicate technical decisions and tradeoffs clearly to both technical and non-technical partners.
Plaid powers millions of people's financial lives by connecting them to apps and services they want to use. The company works with thousands of companies including Venmo, SoFi, Fortune 500 companies, and major banks. Plaid's network covers 12,000 financial institutions across the US, Canada, UK, and Europe.
REQUIREMENTS:
- 6+ years of experience in machine learning, including deploying models into real-world, customer-facing systems
- High agency and creativity, with experience identifying, defining, and proposing high-impact machine learning opportunities
- Ability to analyze large and complex financial datasets and derive actionable insights
- Experience taking machine learning systems from experimentation or proof of concept through production and ongoing improvement
- Proficiency in SQL and Python, as well as data visualization and analysis tools
- Ability to clearly communicate complex technical systems, decisions, tradeoffs, and outcomes to cross-functional partners
- Advanced degree or equivalent work experience in Statistics, Economics, Mathematics, Data Science, or a related field
