Ridvan Ozturac
Engineering Team Lead, Uber Eats Trendyol Go
Istanbul, Türkiye
about
My focus: building reliable systems and teams that don't need me to run them.
I'm an Engineering Team Lead at Uber Eats Trendyol Go, working on the systems behind high-volume commerce, from order management and refunds to the services that quietly keep orders moving from checkout to the door.
Over the past decade, I've moved between writing software, designing distributed systems, and leading engineers. That combination shapes how I lead: I care about architecture, reliability, and delivery, but I care just as much about whether a team can make good decisions without waiting for its leader.
I'm particularly drawn to the engineering problems that become painful at scale: capacity, failure modes, resilience, observability, and the complexity that builds up in systems over time. I like turning hidden risks into things we can measure, test, and improve, before production does it for us.
But the work I'm most proud of is people. My goal as a leader is not to become the smartest person in the room or the team's single point of failure. It's to create the conditions for engineers to become owners: clear context, honest feedback, psychological safety, and enough autonomy to make good decisions.
I still write code and stay close to the systems I lead. Not because I need to be involved in every decision, but because I believe good technical leadership starts with understanding the reality of the work.
I'd rather build a team that can outperform me than a team that depends on me.
experience
education
research
TAM: Temporal Attention for Edge-Oriented Short-Term Load Forecasting
A temporal attention mechanism on a reservoir-recurrent (ESN-GRU) architecture that weights informative time steps to sharpen short-term load forecasting on edge devices.
CAPTAIN: A Testbed for Co-Simulation of Scalable Serverless Computing Environments for AIoT-Enabled Predictive Maintenance
Co-simulation testbed for serverless environments supporting predictive maintenance in Industry 4.0 settings.
iFaaSBus: A Security and Privacy Based Lightweight Framework for Serverless Computing using IoT and Machine Learning
Co-authored framework combining IoT, ML, and serverless (FaaS) for dynamic, privacy-preserving resource scaling.