Senior Machine Learning Engineer - Embedded Insights
Plaid
- Location
- New York City Office
- Employment
- Full Time
- Work model
- Remote
- Level
- Senior
- H-1B history
- 9 approvals (FY2023)
- Posted
- 2h ago
Skills
About this role
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.
About the Team
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.
About the Role
As a Senior Machine Learning Engineer on Embedded Insights, you will help shape Plaid’s future by building machine learning-powered products and features. You will initially support the Plaid App, working on a 0-to-1 consumer-facing product and helping establish product-market fit for a new business line. You will work closely with product managers, data scientists, engineers, customers, and other machine learning engineers to translate ambiguous opportunities into effective ML systems that create measurable customer value. In supporting the Plaid App, you will: Build machine learning-based features for a 0-to-1 consumer-facing product. Partner with product managers to translate ambiguous business requirements into machine learning problems and influence product strategy and roadmap decisions. Rapidly iterate and experiment to help drive product-market fit for a new business line. Work with Data Scientists to define success metrics and guardrails for new machine learning features. Partner with MLEs across product areas to build effective data feedback loops. As a member of the broader Embedded Insights team, you will: Analyze Plaid’s unique datasets to identify high-impact opportunities for machine learning and complete proofs of concept to validate them. Embed with product teams and work closely with product and engineering partners to productionize models and deploy them in real-world, customer-facing products. Optimize and maintain the health of existing models by developing new features, identifying effective retraining cadences, and creating metrics, alerts, and dashboards to monitor performance. Communicate technical decisions, tradeoffs, and system behavior clearly to both technical and non-technical partners. What Excites You Shaping Plaid’s future as intelligence products become a core part of the company’s value proposition. Working with one of the industry’s most unique datasets and helping define how Plaid can use it to create customer value. Identifying and validating new machine learning opportunities across Plaid’s product suite. Working across multiple product areas and developing a deep understanding of Plaid’s products and customers. Building products that empower millions of people to achieve greater financial freedom and opportunity. Working closely with customers to ensure products meet their needs and demonstrate meaningful impact. Joining a high-ownership team where the greenfield opportunity is substantial. What Excites Us 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