Can Altıniğne is a software engineer with 10 years of experience building production-grade ML and data systems, currently working on Core Data Acquisition SRE at Google after impactful ML engineering at Lyft. He has end-to-end experience from data collection and feature engineering to model deployment and monitoring, migrating dozens of models to scalable serving platforms and instrumenting observability with Prometheus/Grafana. His work includes boosting revenue through a LightGBM-based no-show fee system, improving search relevance with list-wise ranking and location embeddings, and shipping high-performing detectors and neural taggers with strong AUC/precision metrics. With a background in computer vision research at EPFL and the Swiss Data Science Center, he combines rigorous academic results (state-of-the-art segmentation and pose/height estimation) with practical cloud-native tooling (Spark, Kubernetes, MLflow, Docker). Based in Munich, he pairs a pragmatic engineering mindset with research-driven creativity, often bridging Go-based service integrations and Python ML stacks to deliver measurable business impact.
10 years of coding experience
8 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at EPFL
Bachelor of Science - BS Computer Engineering, Bachelor of Science - BS Computer Engineering at Istanbul Technical University
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