Machine Learning Engineering Manager, Personalize Intelligence
crypto:applicationengineeringM2Development
Compensation
Not disclosed
This is Adyen
Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition.
For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster.
Machine Learning Engineering Manager, Personalize Intelligence
The Opportunity
We’re looking for an enthusiastic, self-driven Engineering Manager to lead the Personalize Intelligence team. You will lead the team that develops and owns the machine-learning behind Adyen Checkout optimization: our real-time, decision engine that helps merchants to increase their shopper conversion rate to boost seamless checkout experience. It is also the cornerstone of Adyen Uplift, a powerful AI product suite to optimize holistically for conversion, fraud and cost that is used by many of Adyen’s customers today.
As an Engineering Manager, you will build, mentor, and coach a diverse and talented team of machine learning scientists and data engineers. You should be comfortable streamlining the team's engineering operations, refining product requirements together with product and merchants and encouraging effective collaboration. As a critical role in the continued success of our organization, you will help to iterate our culture and build an amazing team environment that will create future leaders for Adyen.
What You'll Do:
Lead the Personalize Intelligence team with hands-on technical leadership, driving architecture strategy and raising the bar through active mentoring and technical guidance.
Work cross-functionally with Design, Product, Data En