About the opportunity
As the world's pioneering local delivery platform, Delivery Hero's mission is to deliver an amazing experience, fast, easy, and to your door. The company operates in over 70+ countries worldwide, powered by tech, designed by people. As one of Europe's largest tech platforms, headquartered in Berlin, Germany, Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index. Delivery Hero enables creative minds to deliver solutions that create impact within their ecosystem.
Your Mission
- Lead the teams responsible for the foundational components of our customer time predictions components.
- Ensure the high reliability of multiple low-latency high-throughput systems that power time predictions. This includes improving domain-level SLOs and SLAs, maintaining a well trained on-call rotation and incident analysis and follow-up.
- Collaborate with Product, Operations and Analytics to ensure engineering has maximum impact on business KPIs.
- Coordinate with stakeholders and across teams and work with other domain leaders in Logistics and in all Regional Brands to ensure seamless integrations.
- Manage and mentor engineering managers and senior ICs across three squads. Establish a strong delegation framework so decisions happen closest to the context. Build a durable second layer of leadership and attract top engineering talent.
- Shape the Long-term Domain Vision: Translate tribe-level objectives into a clear technical roadmap. Balance feature development with reliability, cost efficiency, and modernization initiatives.
What you need to be successful
- You are familiar with the Kotlin/JVM, Kubernetes, Redis and programming language agnostic with a clear understanding of core concepts, and paradigms, and can abstract this knowledge to multiple scenarios.
- You are a knowledgeable technical guide, with min. 2 years of lead of leading squads through managers, who aligns with and supports product and business goals.
- You have min 2 years experience of working close enough with Machine Learning to understand the pros/cons of different models and architectures, key statistical concepts, experiment designs, training, inference, and monitoring of live-serving models in the context of low latency and high throughput.
- You are comfortable with both API-based (gRPC) and event-based communication (SNS/SQS, Kafka).
- You believe in cross-functional teams (Backend, Frontend/Mobile, DataScience, Operations, Analytics) and have experience managing dependencies across tasks and teams.
- You have experience working with IaaC setups; most of our infrastructure runs on Kubernetes deployed with Helm and terraform in AWS.